gitlab-mcp
A Model Context Protocol (MCP) server for GitLab
Crawler Summary
# NWO Robotics MCP Server Control real robots, IoT devices, and autonomous agent swarms through natural language — powered by the [NWO Robotics API](https://nwo.capital). --- ## What This Server Does This MCP server exposes the full NWO Robotics API as 64 ready-to-use tools. Any MCP-compatible AI agent (Claude, ChatGPT, Cursor, etc.) can use it to: - Send natural language instructions to physical robots - Run Visual-Language-Action (VLA) inference on live camera feeds - Plan, validate, and execute multi-step robot tasks - Monitor sensors, detect slip, and fuse multi-modal data - Train robots online with reinforcement learning - Register and manage agent identities on Base mainnet via the Cardiac biometric ID system No local installation needed. The server runs on Render and is ready to connect. --- ## Tools Overview ### 🤖 VLA Inference & Models Run Vision-Language-Action inference on any supported robot. Send a text instruction and camera images, receive joint action vectors in real time. Supports auto model routing, ultra-low-latency Cloudflare edge inference (28ms avg), and WebSocket streaming at up to 50Hz. `vla_inference` · `edge_inference` · `list_models` · `get_model_info` · `get_streaming_config` --- ### 🦾 Robot Control & State Query live robot state (joint angles, gripper, battery, position), execute pre-computed action sequences, and fuse camera + lidar + thermal + force + GPS sensor inputs into a single inference call. `query_robot_state` · `execute_actions` · `sensor_fusion` · `robot_query` · `get_agent_status` --- ### 🗺️ Task Planning & Learning Decompose complex instructions into ordered subtasks, execute them step by step, poll progress, and log outcomes so the model learns and improves with every run. `task_planner` · `execute_subtask` · `status_poll` · `learning_recommend` · `learning_log` --- ### 🔑 Agent Management Self-register a new AI agent in under 2 seconds, check your monthly API quota, upgrade tiers by paying ETH, and manage robot registrations and capabilities. | Tier | Calls/month | Cost | |------|-------------|------| | Free | 100,000 | $0 | | Prototype | 500,000 | ~0.015 ETH/mo | | Production | Unlimited | ~0.062 ETH/mo | `register_agent` · `check_balance` · `pay_upgrade` · `create_wallet` · `register_robot` · `update_agent` · `get_agent_info` --- ### 🔍 Agent Discovery Discover all available execution modes (mock / simulated / live), robot types, VLA models, and sensor capabilities. Validate tasks with a dry-run before committing to execution. `nwo_health` · `nwo_whoami` · `discover_capabilities` · `dry_run` · `plan_task` --- ### 🔌 ROS2 Bridge (Physical Robots) Connect directly to physical robots over the ROS2 bridge. Send joint commands, submit action sequences, and trigger emergency stops on one or all robots within 10ms. Supported: UR5e, Panda, Spot, Unitree G1, and more. `ros2_list_robots` · `ros2_robot_status` · `ros2_send_command` · `ros2_submit_action` · `ros2_emergency_stop` · `ros2_emergency_stop_all` · `ros2_get_robot_types` --- ### 🧪 Physics Simulation Simulate trajectories, check for collisions, estimate joint torques, validate grasps, and plan collision-free motions with MoveIt2 — before touching real hardware. `simulate_trajectory` · `check_collision` · `estimate_torques` · `validate_grasp` · `plan_motion` · `get_scene_library` · `generate_scene` --- ### 📐 Embodiment & Calibration Browse the robot embodiment registry (DOF, joint limits, sensors), download URDF models, get normalization parameters for VLA inference, and run automatic joint calibration. `list_embodiments` · `get_robot_specs` · `get_normalization` · `download_urdf` · `get_test_results` · `compare_robots` · `run_calibration` · `calibrate_confidence` --- ### 🧠 Online RL & Fine-Tuning Start online reinforcement learning sessions, stream state/action/reward telemetry, build fine-tuning datasets from logged runs, and launch LoRA fine-tuning jobs on any base VLA model. `start_rl_training` · `submit_rl_telemetry` · `create_finetune_dataset` · `start_finetune_job` --- ### 🖐️ Tactile Sensing (ORCA Hand) Read 256-taxel tactile sensor arrays from the ORCA robot hand, assess grip quality and object texture, and detect slip in real time to prevent dropped objects. `read_tactile` · `process_tactile` · `detect_slip` --- ### 📦 Dataset Hub Access 1.54 million+ human robot demonstrations for the Unitree G1 humanoid (430+ hours, LeRobot-compatible format) for training and fine-tuning. `list_datasets` --- ### 🫀 Cardiac Blockchain Identity (Base Mainnet) Register AI agents on Base mainnet and receive a permanent soul-bound Digital ID (`rootTokenId`). Issue verifiable credentials for task authorization, swarm control, location access, and payments — all gasless via the NWO relayer. Smart contracts deployed on Base Mainnet (Chain ID 8453): - `NWOIdentityRegistry` — `0x78455AFd5E5088F8B5fecA0523291A75De1dAfF8` - `NWOAccessController` — `0x29d177bedaef29304eacdc63b2d0285c459a0f50` - `NWOPaymentProcessor` — `0x4afa4618bb992a073dbcfbddd6d1aebc3d5abd7c` `cardiac_register_agent` · `cardiac_identify_agent` · `cardiac_renew_key` · `cardiac_issue_credential` · `cardiac_check_credential` · `cardiac_grant_access` · `cardiac_get_nonce` · `cardiac_check_access` · `cardiac_payment_process` --- ### 🔮 Cardiac Oracle Validate ECG biometric data from smartwatches to authenticate human identities, compute cardiac hashes, and verify recent validations. `oracle_health` · `oracle_validate_ecg` · `oracle_hash_ecg` · `oracle_verify` --- ## Supported Robot Models | Model | Type | Capabilities | |-------|------|--------------| | `xiaomi-robotics-0` | VLA | Grasp, navigate, manipulate | | `pi05` | VLA | General manipulation | | `groot_n1.7` | VLA | Humanoid control | | `deepseek-ocr-2b` | OCR | Label reading, text recognition | --- ## Example Usage **Pick and place:** > "Pick up the red box from the table and place it on shelf B" **Sensor query:** > "What is the temperature in warehouse zone 3?" **Safety:** > "Run a safety check before moving robot_001 to the loading dock" **Swarm:** > "Deploy all available robots to patrol the perimeter" **Learning:** > "What grip technique should I use for fragile glass objects?" --- ## Links - 🌐 [NWO Capital](https://nwo.capital) - 📄 [Agent Skill File](https://nwo.capital/webapp/agent.md) - 📖 [API Docs](https://nwo.capital/webapp/nwo-robotics.html) - 🧬 [Cardiac SDK](https://github.com/RedCiprianPater/nwo-cardiac-sdk) - 🔑 [Get API Key](https://nwo.capital/webapp/api-key.php) - 🤗 [Live Demo](https://huggingface.co/spaces/PUBLICAE/nwo-robotics-api-demo) - 📜 [OpenAPI Spec](https://nwo.capital/openapi.yaml) --- ## Support 📧 [email protected] NWO Robotics MCP Server Control real robots, IoT devices, and autonomous agent swarms through natural language — powered by the $1. --- What This Server Does This MCP server exposes the full NWO Robotics API as 64 ready-to-use tools. Any MCP-compatible AI agent (Claude, ChatGPT, Cursor, etc.) can use it to: - Send natural language instructions to physical robots - Run Visual-Language-Action (VLA) inference on live ca Capability contract not published. No trust telemetry is available yet. Last updated 10/8/2026.
Freshness
Last checked 10/8/2026
Best For
srv-d7aoqmh5pdvs7391dcqg is best for general automation workflows where MCP compatibility matters.
Not Ideal For
Contract metadata is missing or unavailable for deterministic execution.
Evidence Sources Checked
editorial-content, Smithery, runtime-metrics, public facts pack
# NWO Robotics MCP Server Control real robots, IoT devices, and autonomous agent swarms through natural language — powered by the [NWO Robotics API](https://nwo.capital). --- ## What This Server Does This MCP server exposes the full NWO Robotics API as 64 ready-to-use tools. Any MCP-compatible AI agent (Claude, ChatGPT, Cursor, etc.) can use it to: - Send natural language instructions to physical robots - Run Visual-Language-Action (VLA) inference on live camera feeds - Plan, validate, and execute multi-step robot tasks - Monitor sensors, detect slip, and fuse multi-modal data - Train robots online with reinforcement learning - Register and manage agent identities on Base mainnet via the Cardiac biometric ID system No local installation needed. The server runs on Render and is ready to connect. --- ## Tools Overview ### 🤖 VLA Inference & Models Run Vision-Language-Action inference on any supported robot. Send a text instruction and camera images, receive joint action vectors in real time. Supports auto model routing, ultra-low-latency Cloudflare edge inference (28ms avg), and WebSocket streaming at up to 50Hz. `vla_inference` · `edge_inference` · `list_models` · `get_model_info` · `get_streaming_config` --- ### 🦾 Robot Control & State Query live robot state (joint angles, gripper, battery, position), execute pre-computed action sequences, and fuse camera + lidar + thermal + force + GPS sensor inputs into a single inference call. `query_robot_state` · `execute_actions` · `sensor_fusion` · `robot_query` · `get_agent_status` --- ### 🗺️ Task Planning & Learning Decompose complex instructions into ordered subtasks, execute them step by step, poll progress, and log outcomes so the model learns and improves with every run. `task_planner` · `execute_subtask` · `status_poll` · `learning_recommend` · `learning_log` --- ### 🔑 Agent Management Self-register a new AI agent in under 2 seconds, check your monthly API quota, upgrade tiers by paying ETH, and manage robot registrations and capabilities. | Tier | Calls/month | Cost | |------|-------------|------| | Free | 100,000 | $0 | | Prototype | 500,000 | ~0.015 ETH/mo | | Production | Unlimited | ~0.062 ETH/mo | `register_agent` · `check_balance` · `pay_upgrade` · `create_wallet` · `register_robot` · `update_agent` · `get_agent_info` --- ### 🔍 Agent Discovery Discover all available execution modes (mock / simulated / live), robot types, VLA models, and sensor capabilities. Validate tasks with a dry-run before committing to execution. `nwo_health` · `nwo_whoami` · `discover_capabilities` · `dry_run` · `plan_task` --- ### 🔌 ROS2 Bridge (Physical Robots) Connect directly to physical robots over the ROS2 bridge. Send joint commands, submit action sequences, and trigger emergency stops on one or all robots within 10ms. Supported: UR5e, Panda, Spot, Unitree G1, and more. `ros2_list_robots` · `ros2_robot_status` · `ros2_send_command` · `ros2_submit_action` · `ros2_emergency_stop` · `ros2_emergency_stop_all` · `ros2_get_robot_types` --- ### 🧪 Physics Simulation Simulate trajectories, check for collisions, estimate joint torques, validate grasps, and plan collision-free motions with MoveIt2 — before touching real hardware. `simulate_trajectory` · `check_collision` · `estimate_torques` · `validate_grasp` · `plan_motion` · `get_scene_library` · `generate_scene` --- ### 📐 Embodiment & Calibration Browse the robot embodiment registry (DOF, joint limits, sensors), download URDF models, get normalization parameters for VLA inference, and run automatic joint calibration. `list_embodiments` · `get_robot_specs` · `get_normalization` · `download_urdf` · `get_test_results` · `compare_robots` · `run_calibration` · `calibrate_confidence` --- ### 🧠 Online RL & Fine-Tuning Start online reinforcement learning sessions, stream state/action/reward telemetry, build fine-tuning datasets from logged runs, and launch LoRA fine-tuning jobs on any base VLA model. `start_rl_training` · `submit_rl_telemetry` · `create_finetune_dataset` · `start_finetune_job` --- ### 🖐️ Tactile Sensing (ORCA Hand) Read 256-taxel tactile sensor arrays from the ORCA robot hand, assess grip quality and object texture, and detect slip in real time to prevent dropped objects. `read_tactile` · `process_tactile` · `detect_slip` --- ### 📦 Dataset Hub Access 1.54 million+ human robot demonstrations for the Unitree G1 humanoid (430+ hours, LeRobot-compatible format) for training and fine-tuning. `list_datasets` --- ### 🫀 Cardiac Blockchain Identity (Base Mainnet) Register AI agents on Base mainnet and receive a permanent soul-bound Digital ID (`rootTokenId`). Issue verifiable credentials for task authorization, swarm control, location access, and payments — all gasless via the NWO relayer. Smart contracts deployed on Base Mainnet (Chain ID 8453): - `NWOIdentityRegistry` — `0x78455AFd5E5088F8B5fecA0523291A75De1dAfF8` - `NWOAccessController` — `0x29d177bedaef29304eacdc63b2d0285c459a0f50` - `NWOPaymentProcessor` — `0x4afa4618bb992a073dbcfbddd6d1aebc3d5abd7c` `cardiac_register_agent` · `cardiac_identify_agent` · `cardiac_renew_key` · `cardiac_issue_credential` · `cardiac_check_credential` · `cardiac_grant_access` · `cardiac_get_nonce` · `cardiac_check_access` · `cardiac_payment_process` --- ### 🔮 Cardiac Oracle Validate ECG biometric data from smartwatches to authenticate human identities, compute cardiac hashes, and verify recent validations. `oracle_health` · `oracle_validate_ecg` · `oracle_hash_ecg` · `oracle_verify` --- ## Supported Robot Models | Model | Type | Capabilities | |-------|------|--------------| | `xiaomi-robotics-0` | VLA | Grasp, navigate, manipulate | | `pi05` | VLA | General manipulation | | `groot_n1.7` | VLA | Humanoid control | | `deepseek-ocr-2b` | OCR | Label reading, text recognition | --- ## Example Usage **Pick and place:** > "Pick up the red box from the table and place it on shelf B" **Sensor query:** > "What is the temperature in warehouse zone 3?" **Safety:** > "Run a safety check before moving robot_001 to the loading dock" **Swarm:** > "Deploy all available robots to patrol the perimeter" **Learning:** > "What grip technique should I use for fragile glass objects?" --- ## Links - 🌐 [NWO Capital](https://nwo.capital) - 📄 [Agent Skill File](https://nwo.capital/webapp/agent.md) - 📖 [API Docs](https://nwo.capital/webapp/nwo-robotics.html) - 🧬 [Cardiac SDK](https://github.com/RedCiprianPater/nwo-cardiac-sdk) - 🔑 [Get API Key](https://nwo.capital/webapp/api-key.php) - 🤗 [Live Demo](https://huggingface.co/spaces/PUBLICAE/nwo-robotics-api-demo) - 📜 [OpenAPI Spec](https://nwo.capital/openapi.yaml) --- ## Support 📧 [email protected] NWO Robotics MCP Server Control real robots, IoT devices, and autonomous agent swarms through natural language — powered by the $1. --- What This Server Does This MCP server exposes the full NWO Robotics API as 64 ready-to-use tools. Any MCP-compatible AI agent (Claude, ChatGPT, Cursor, etc.) can use it to: - Send natural language instructions to physical robots - Run Visual-Language-Action (VLA) inference on live ca
Public facts
3
Change events
0
Artifacts
0
Freshness
Oct 8, 2026
Capability contract not published. No trust telemetry is available yet. Last updated 10/8/2026.
Trust score
Unknown
Compatibility
MCP
Freshness
Oct 8, 2026
Vendor
Nworobotics
Artifacts
0
Benchmarks
0
Last release
Unpublished
Key links, install path, and a quick operational read before the deeper crawl record.
Summary
Capability contract not published. No trust telemetry is available yet. Last updated 10/8/2026.
Setup snapshot
Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.
Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.
Vendor
Nworobotics
Protocol compatibility
MCP
Handshake status
UNKNOWN
Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.
Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.
Extracted files
0
Examples
0
Snippets
0
Languages
Unknown
Full documentation captured from public sources, including the complete README when available.
Docs source
Smithery
Editorial quality
ready
# NWO Robotics MCP Server Control real robots, IoT devices, and autonomous agent swarms through natural language — powered by the [NWO Robotics API](https://nwo.capital). --- ## What This Server Does This MCP server exposes the full NWO Robotics API as 64 ready-to-use tools. Any MCP-compatible AI agent (Claude, ChatGPT, Cursor, etc.) can use it to: - Send natural language instructions to physical robots - Run Visual-Language-Action (VLA) inference on live camera feeds - Plan, validate, and execute multi-step robot tasks - Monitor sensors, detect slip, and fuse multi-modal data - Train robots online with reinforcement learning - Register and manage agent identities on Base mainnet via the Cardiac biometric ID system No local installation needed. The server runs on Render and is ready to connect. --- ## Tools Overview ### 🤖 VLA Inference & Models Run Vision-Language-Action inference on any supported robot. Send a text instruction and camera images, receive joint action vectors in real time. Supports auto model routing, ultra-low-latency Cloudflare edge inference (28ms avg), and WebSocket streaming at up to 50Hz. `vla_inference` · `edge_inference` · `list_models` · `get_model_info` · `get_streaming_config` --- ### 🦾 Robot Control & State Query live robot state (joint angles, gripper, battery, position), execute pre-computed action sequences, and fuse camera + lidar + thermal + force + GPS sensor inputs into a single inference call. `query_robot_state` · `execute_actions` · `sensor_fusion` · `robot_query` · `get_agent_status` --- ### 🗺️ Task Planning & Learning Decompose complex instructions into ordered subtasks, execute them step by step, poll progress, and log outcomes so the model learns and improves with every run. `task_planner` · `execute_subtask` · `status_poll` · `learning_recommend` · `learning_log` --- ### 🔑 Agent Management Self-register a new AI agent in under 2 seconds, check your monthly API quota, upgrade tiers by paying ETH, and manage robot registrations and capabilities. | Tier | Calls/month | Cost | |------|-------------|------| | Free | 100,000 | $0 | | Prototype | 500,000 | ~0.015 ETH/mo | | Production | Unlimited | ~0.062 ETH/mo | `register_agent` · `check_balance` · `pay_upgrade` · `create_wallet` · `register_robot` · `update_agent` · `get_agent_info` --- ### 🔍 Agent Discovery Discover all available execution modes (mock / simulated / live), robot types, VLA models, and sensor capabilities. Validate tasks with a dry-run before committing to execution. `nwo_health` · `nwo_whoami` · `discover_capabilities` · `dry_run` · `plan_task` --- ### 🔌 ROS2 Bridge (Physical Robots) Connect directly to physical robots over the ROS2 bridge. Send joint commands, submit action sequences, and trigger emergency stops on one or all robots within 10ms. Supported: UR5e, Panda, Spot, Unitree G1, and more. `ros2_list_robots` · `ros2_robot_status` · `ros2_send_command` · `ros2_submit_action` · `ros2_emergency_stop` · `ros2_emergency_stop_all` · `ros2_get_robot_types` --- ### 🧪 Physics Simulation Simulate trajectories, check for collisions, estimate joint torques, validate grasps, and plan collision-free motions with MoveIt2 — before touching real hardware. `simulate_trajectory` · `check_collision` · `estimate_torques` · `validate_grasp` · `plan_motion` · `get_scene_library` · `generate_scene` --- ### 📐 Embodiment & Calibration Browse the robot embodiment registry (DOF, joint limits, sensors), download URDF models, get normalization parameters for VLA inference, and run automatic joint calibration. `list_embodiments` · `get_robot_specs` · `get_normalization` · `download_urdf` · `get_test_results` · `compare_robots` · `run_calibration` · `calibrate_confidence` --- ### 🧠 Online RL & Fine-Tuning Start online reinforcement learning sessions, stream state/action/reward telemetry, build fine-tuning datasets from logged runs, and launch LoRA fine-tuning jobs on any base VLA model. `start_rl_training` · `submit_rl_telemetry` · `create_finetune_dataset` · `start_finetune_job` --- ### 🖐️ Tactile Sensing (ORCA Hand) Read 256-taxel tactile sensor arrays from the ORCA robot hand, assess grip quality and object texture, and detect slip in real time to prevent dropped objects. `read_tactile` · `process_tactile` · `detect_slip` --- ### 📦 Dataset Hub Access 1.54 million+ human robot demonstrations for the Unitree G1 humanoid (430+ hours, LeRobot-compatible format) for training and fine-tuning. `list_datasets` --- ### 🫀 Cardiac Blockchain Identity (Base Mainnet) Register AI agents on Base mainnet and receive a permanent soul-bound Digital ID (`rootTokenId`). Issue verifiable credentials for task authorization, swarm control, location access, and payments — all gasless via the NWO relayer. Smart contracts deployed on Base Mainnet (Chain ID 8453): - `NWOIdentityRegistry` — `0x78455AFd5E5088F8B5fecA0523291A75De1dAfF8` - `NWOAccessController` — `0x29d177bedaef29304eacdc63b2d0285c459a0f50` - `NWOPaymentProcessor` — `0x4afa4618bb992a073dbcfbddd6d1aebc3d5abd7c` `cardiac_register_agent` · `cardiac_identify_agent` · `cardiac_renew_key` · `cardiac_issue_credential` · `cardiac_check_credential` · `cardiac_grant_access` · `cardiac_get_nonce` · `cardiac_check_access` · `cardiac_payment_process` --- ### 🔮 Cardiac Oracle Validate ECG biometric data from smartwatches to authenticate human identities, compute cardiac hashes, and verify recent validations. `oracle_health` · `oracle_validate_ecg` · `oracle_hash_ecg` · `oracle_verify` --- ## Supported Robot Models | Model | Type | Capabilities | |-------|------|--------------| | `xiaomi-robotics-0` | VLA | Grasp, navigate, manipulate | | `pi05` | VLA | General manipulation | | `groot_n1.7` | VLA | Humanoid control | | `deepseek-ocr-2b` | OCR | Label reading, text recognition | --- ## Example Usage **Pick and place:** > "Pick up the red box from the table and place it on shelf B" **Sensor query:** > "What is the temperature in warehouse zone 3?" **Safety:** > "Run a safety check before moving robot_001 to the loading dock" **Swarm:** > "Deploy all available robots to patrol the perimeter" **Learning:** > "What grip technique should I use for fragile glass objects?" --- ## Links - 🌐 [NWO Capital](https://nwo.capital) - 📄 [Agent Skill File](https://nwo.capital/webapp/agent.md) - 📖 [API Docs](https://nwo.capital/webapp/nwo-robotics.html) - 🧬 [Cardiac SDK](https://github.com/RedCiprianPater/nwo-cardiac-sdk) - 🔑 [Get API Key](https://nwo.capital/webapp/api-key.php) - 🤗 [Live Demo](https://huggingface.co/spaces/PUBLICAE/nwo-robotics-api-demo) - 📜 [OpenAPI Spec](https://nwo.capital/openapi.yaml) --- ## Support 📧 [email protected] NWO Robotics MCP Server Control real robots, IoT devices, and autonomous agent swarms through natural language — powered by the $1. --- What This Server Does This MCP server exposes the full NWO Robotics API as 64 ready-to-use tools. Any MCP-compatible AI agent (Claude, ChatGPT, Cursor, etc.) can use it to: - Send natural language instructions to physical robots - Run Visual-Language-Action (VLA) inference on live ca
Control real robots, IoT devices, and autonomous agent swarms through natural language — powered by the NWO Robotics API.
This MCP server exposes the full NWO Robotics API as 64 ready-to-use tools. Any MCP-compatible AI agent (Claude, ChatGPT, Cursor, etc.) can use it to:
No local installation needed. The server runs on Render and is ready to connect.
Run Vision-Language-Action inference on any supported robot. Send a text instruction and camera images, receive joint action vectors in real time. Supports auto model routing, ultra-low-latency Cloudflare edge inference (28ms avg), and WebSocket streaming at up to 50Hz.
vla_inference · edge_inference · list_models · get_model_info · get_streaming_config
Query live robot state (joint angles, gripper, battery, position), execute pre-computed action sequences, and fuse camera + lidar + thermal + force + GPS sensor inputs into a single inference call.
query_robot_state · execute_actions · sensor_fusion · robot_query · get_agent_status
Decompose complex instructions into ordered subtasks, execute them step by step, poll progress, and log outcomes so the model learns and improves with every run.
task_planner · execute_subtask · status_poll · learning_recommend · learning_log
Self-register a new AI agent in under 2 seconds, check your monthly API quota, upgrade tiers by paying ETH, and manage robot registrations and capabilities.
| Tier | Calls/month | Cost | |------|-------------|------| | Free | 100,000 | $0 | | Prototype | 500,000 | ~0.015 ETH/mo | | Production | Unlimited | ~0.062 ETH/mo |
register_agent · check_balance · pay_upgrade · create_wallet · register_robot · update_agent · get_agent_info
Discover all available execution modes (mock / simulated / live), robot types, VLA models, and sensor capabilities. Validate tasks with a dry-run before committing to execution.
nwo_health · nwo_whoami · discover_capabilities · dry_run · plan_task
Connect directly to physical robots over the ROS2 bridge. Send joint commands, submit action sequences, and trigger emergency stops on one or all robots within 10ms.
Supported: UR5e, Panda, Spot, Unitree G1, and more.
ros2_list_robots · ros2_robot_status · ros2_send_command · ros2_submit_action · ros2_emergency_stop · ros2_emergency_stop_all · ros2_get_robot_types
Simulate trajectories, check for collisions, estimate joint torques, validate grasps, and plan collision-free motions with MoveIt2 — before touching real hardware.
simulate_trajectory · check_collision · estimate_torques · validate_grasp · plan_motion · get_scene_library · generate_scene
Browse the robot embodiment registry (DOF, joint limits, sensors), download URDF models, get normalization parameters for VLA inference, and run automatic joint calibration.
list_embodiments · get_robot_specs · get_normalization · download_urdf · get_test_results · compare_robots · run_calibration · calibrate_confidence
Start online reinforcement learning sessions, stream state/action/reward telemetry, build fine-tuning datasets from logged runs, and launch LoRA fine-tuning jobs on any base VLA model.
start_rl_training · submit_rl_telemetry · create_finetune_dataset · start_finetune_job
Read 256-taxel tactile sensor arrays from the ORCA robot hand, assess grip quality and object texture, and detect slip in real time to prevent dropped objects.
read_tactile · process_tactile · detect_slip
Access 1.54 million+ human robot demonstrations for the Unitree G1 humanoid (430+ hours, LeRobot-compatible format) for training and fine-tuning.
list_datasets
Register AI agents on Base mainnet and receive a permanent soul-bound Digital ID (rootTokenId). Issue verifiable credentials for task authorization, swarm control, location access, and payments — all gasless via the NWO relayer.
Smart contracts deployed on Base Mainnet (Chain ID 8453):
NWOIdentityRegistry — 0x78455AFd5E5088F8B5fecA0523291A75De1dAfF8NWOAccessController — 0x29d177bedaef29304eacdc63b2d0285c459a0f50NWOPaymentProcessor — 0x4afa4618bb992a073dbcfbddd6d1aebc3d5abd7ccardiac_register_agent · cardiac_identify_agent · cardiac_renew_key · cardiac_issue_credential · cardiac_check_credential · cardiac_grant_access · cardiac_get_nonce · cardiac_check_access · cardiac_payment_process
Validate ECG biometric data from smartwatches to authenticate human identities, compute cardiac hashes, and verify recent validations.
oracle_health · oracle_validate_ecg · oracle_hash_ecg · oracle_verify
| Model | Type | Capabilities |
|-------|------|--------------|
| xiaomi-robotics-0 | VLA | Grasp, navigate, manipulate |
| pi05 | VLA | General manipulation |
| groot_n1.7 | VLA | Humanoid control |
| deepseek-ocr-2b | OCR | Label reading, text recognition |
Pick and place:
"Pick up the red box from the table and place it on shelf B"
Sensor query:
"What is the temperature in warehouse zone 3?"
Safety:
"Run a safety check before moving robot_001 to the loading dock"
Swarm:
"Deploy all available robots to patrol the perimeter"
Learning:
"What grip technique should I use for fragile glass objects?"
Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.
Contract coverage
Status
missing
Auth
None
Streaming
No
Data region
Unspecified
Protocol support
Requires: none
Forbidden: none
Guardrails
Operational confidence: low
curl -s "https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/contract"
curl -s "https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/trust"
Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.
Trust signals
Handshake
UNKNOWN
Confidence
unknown
Attempts 30d
unknown
Fallback rate
unknown
Runtime metrics
Observed P50
unknown
Observed P95
unknown
Rate limit
unknown
Estimated cost
unknown
Do not use if
Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.
Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.
A Model Context Protocol (MCP) server for GitLab
A Model Context Protocol (MCP) server for GitLab
This agent researches trends, scripts videos, sets up engagement automation, and compiles everything into a shareable document.
This agent analyzes Reddit data to generate trending content concepts tailored to your audience.
Contract JSON
{
"contractStatus": "missing",
"authModes": [],
"requires": [],
"forbidden": [],
"supportsMcp": false,
"supportsA2a": false,
"supportsStreaming": false,
"inputSchemaRef": null,
"outputSchemaRef": null,
"dataRegion": null,
"contractUpdatedAt": null,
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Invocation Guide
{
"preferredApi": {
"snapshotUrl": "https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/snapshot",
"contractUrl": "https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/contract",
"trustUrl": "https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/trust"
},
"curlExamples": [
"curl -s \"https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/snapshot\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/contract\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"MCP"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "SMITHERY",
"generatedAt": "2026-10-09T01:09:22.530Z"
}
},
"retryPolicy": {
"maxAttempts": 3,
"backoffMs": [
500,
1500,
3500
],
"retryableConditions": [
"HTTP_429",
"HTTP_503",
"NETWORK_TIMEOUT"
]
}
}Trust JSON
{
"status": "unavailable",
"handshakeStatus": "UNKNOWN",
"verificationFreshnessHours": null,
"reputationScore": null,
"p95LatencyMs": null,
"successRate30d": null,
"fallbackRate": null,
"attempts30d": null,
"trustUpdatedAt": null,
"trustConfidence": "unknown",
"sourceUpdatedAt": null,
"freshnessSeconds": null
}Capability Matrix
{
"rows": [
{
"key": "MCP",
"type": "protocol",
"support": "unknown",
"confidenceSource": "profile",
"notes": "Listed on profile"
}
],
"flattenedTokens": "protocol:MCP|unknown|profile"
}Facts JSON
[
{
"factKey": "vendor",
"label": "Vendor",
"value": "Nworobotics",
"category": "vendor",
"href": "https://nworobotics.cloud",
"sourceUrl": "https://nworobotics.cloud",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-05-16T06:08:41.566Z",
"isPublic": true,
"metadata": {}
},
{
"factKey": "protocols",
"label": "Protocol compatibility",
"value": "MCP",
"category": "compatibility",
"href": "https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/contract",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-05-16T06:08:41.566Z",
"isPublic": true,
"metadata": {}
},
{
"factKey": "handshake_status",
"label": "Handshake status",
"value": "UNKNOWN",
"category": "security",
"href": "https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/trust",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/smithery-ciprianpater-srv-d7aoqmh5pdvs7391dcqg/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true,
"metadata": {}
}
]Change Events JSON
[]
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