AionUi
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Crawler Summary
CrewAI Agent and MCP Server to give review about your chess performance from lichess ChessAI — Lichess MCP Server An MCP (Model Context Protocol) server that exposes Lichess player data as tools, resources, and prompts — usable directly from Claude Desktop or any MCP-compatible client. What's inside | File | Purpose | |---|---| | lichess_mcp.py | MCP server — tools, resources, prompts | | lichess_tools.py | Raw Lichess API helpers (used by CrewAI agent) | | agent.py | Standalone CrewAI agent for CLI Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.
Freshness
Last checked 10/9/2026
Best For
ChessAI is best for crewai, multi-agent workflows where OpenClaw compatibility matters.
Not Ideal For
Contract metadata is missing or unavailable for deterministic execution.
Evidence Sources Checked
editorial-content, GITHUB REPOS, runtime-metrics, public facts pack
CrewAI Agent and MCP Server to give review about your chess performance from lichess ChessAI — Lichess MCP Server An MCP (Model Context Protocol) server that exposes Lichess player data as tools, resources, and prompts — usable directly from Claude Desktop or any MCP-compatible client. What's inside | File | Purpose | |---|---| | lichess_mcp.py | MCP server — tools, resources, prompts | | lichess_tools.py | Raw Lichess API helpers (used by CrewAI agent) | | agent.py | Standalone CrewAI agent for CLI
Public facts
4
Change events
1
Artifacts
0
Freshness
Oct 9, 2026
Capability contract not published. No trust telemetry is available yet. Last updated 10/9/2026.
Trust score
Unknown
Compatibility
OpenClaw
Freshness
Oct 9, 2026
Vendor
Nagarjung91
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Unpublished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 10/9/2026.
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
Nagarjung91
Protocol compatibility
OpenClaw
Handshake status
UNKNOWN
Crawlable docs
6 indexed pages on the official domain
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
6
Snippets
0
Languages
python
sh
python3 -m venv venv && source venv/bin/activate pip install -r requirements.txt
sh
cp .env.example .env
env
AZURE_API_KEY=your-azure-openai-key AZURE_API_BASE=https://your-endpoint.openai.azure.com/ AZURE_API_VERSION=2024-12-01-preview DEFAULT_LICHESS_USER=your-lichess-username LANGFUSE_PUBLIC_KEY=pk-lf-... LANGFUSE_SECRET_KEY=sk-lf-... LANGFUSE_HOST=https://us.cloud.langfuse.com
json
{
"mcpServers": {
"lichess-chess-coach": {
"command": "/path/to/venv/bin/python3",
"args": ["/path/to/lichess_mcp.py"],
"env": {
"DEFAULT_LICHESS_USER": "your-lichess-username"
}
}
}
}sh
source venv/bin/activate mcp dev lichess_mcp.py
sh
source venv/bin/activate python3 agent.py
Full documentation captured from public sources, including the complete README when available.
Docs source
GITHUB REPOS
Editorial quality
ready
CrewAI Agent and MCP Server to give review about your chess performance from lichess ChessAI — Lichess MCP Server An MCP (Model Context Protocol) server that exposes Lichess player data as tools, resources, and prompts — usable directly from Claude Desktop or any MCP-compatible client. What's inside | File | Purpose | |---|---| | lichess_mcp.py | MCP server — tools, resources, prompts | | lichess_tools.py | Raw Lichess API helpers (used by CrewAI agent) | | agent.py | Standalone CrewAI agent for CLI
An MCP (Model Context Protocol) server that exposes Lichess player data as tools, resources, and prompts — usable directly from Claude Desktop or any MCP-compatible client.
| File | Purpose |
|---|---|
| lichess_mcp.py | MCP server — tools, resources, prompts |
| lichess_tools.py | Raw Lichess API helpers (used by CrewAI agent) |
| agent.py | Standalone CrewAI agent for CLI use |
| Tool | Description |
|---|---|
| get_lichess_perfs | All ratings across every format |
| get_lichess_rating_history | Full rating timeline |
| get_lichess_performance | Detailed stats for one format (bullet, blitz, rapid, etc.) |
| get_lichess_profile | Full public profile |
lichess://player/{username}/profile — formatted profile cardlichess://player/{username}/rating-history — rating history summarycoach_player — coaching analysis for a player + formatcompare_formats — compare performance across all formatsClone the repo and create a virtual environment:
python3 -m venv venv && source venv/bin/activate
pip install -r requirements.txt
Copy .env.example and fill in your keys:
cp .env.example .env
AZURE_API_KEY=your-azure-openai-key
AZURE_API_BASE=https://your-endpoint.openai.azure.com/
AZURE_API_VERSION=2024-12-01-preview
DEFAULT_LICHESS_USER=your-lichess-username
LANGFUSE_PUBLIC_KEY=pk-lf-...
LANGFUSE_SECRET_KEY=sk-lf-...
LANGFUSE_HOST=https://us.cloud.langfuse.com
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"lichess-chess-coach": {
"command": "/path/to/venv/bin/python3",
"args": ["/path/to/lichess_mcp.py"],
"env": {
"DEFAULT_LICHESS_USER": "your-lichess-username"
}
}
}
}
Restart Claude Desktop. The tools will be available immediately in any chat.
source venv/bin/activate
mcp dev lichess_mcp.py
Opens the inspector UI at http://localhost:6274.
source venv/bin/activate
python3 agent.py
All tool calls are traced via Langfuse — inputs, outputs, and latency are captured automatically. Set your Langfuse keys in .env to enable.
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/crewai-nagarjung91-chessai/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/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.
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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/crewai-nagarjung91-chessai/snapshot",
"contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/contract",
"trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/trust"
},
"curlExamples": [
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/snapshot\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/contract\"",
"curl -s \"https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/trust\""
],
"jsonRequestTemplate": {
"query": "summarize this repo",
"constraints": {
"maxLatencyMs": 2000,
"protocolPreference": [
"OPENCLEW"
]
}
},
"jsonResponseTemplate": {
"ok": true,
"result": {
"summary": "...",
"confidence": 0.9
},
"meta": {
"source": "GITHUB_REPOS",
"generatedAt": "2026-10-09T22:49:11.637Z"
}
},
"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": "OPENCLEW",
"type": "protocol",
"support": "unknown",
"confidenceSource": "profile",
"notes": "Listed on profile"
},
{
"key": "crewai",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
},
{
"key": "multi-agent",
"type": "capability",
"support": "supported",
"confidenceSource": "profile",
"notes": "Declared in agent profile metadata"
}
],
"flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:crewai|supported|profile capability:multi-agent|supported|profile"
}Facts JSON
[
{
"factKey": "vendor",
"category": "vendor",
"label": "Vendor",
"value": "Nagarjung91",
"href": "https://github.com/NagarjunG91/ChessAI",
"sourceUrl": "https://github.com/NagarjunG91/ChessAI",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-10-09T19:19:45.600Z",
"isPublic": true
},
{
"factKey": "protocols",
"category": "compatibility",
"label": "Protocol compatibility",
"value": "OpenClaw",
"href": "https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/contract",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/contract",
"sourceType": "contract",
"confidence": "medium",
"observedAt": "2026-10-09T19:19:45.600Z",
"isPublic": true
},
{
"factKey": "docs_crawl",
"category": "integration",
"label": "Crawlable docs",
"value": "6 indexed pages on the official domain",
"href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-04-15T05:03:46.393Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/trust",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-nagarjung91-chessai/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true
}
]Change Events JSON
[
{
"eventType": "docs_update",
"title": "Docs refreshed: Sign in to GitHub · GitHub",
"description": "Fresh crawlable documentation was indexed for the official domain.",
"href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
"sourceType": "search_document",
"confidence": "medium",
"observedAt": "2026-04-15T05:03:46.393Z",
"isPublic": true
}
]Sponsored
Ads related to ChessAI and adjacent AI workflows.