Crawler Summary

Build-Agentic-AI-and-Gen-AI-Agents-with-MCP answer-first brief

Model Context Protocol (MCP) Bootcamp offers a deep dive into MCP architecture and its role in the Agentic AI ecosystem. Learn to build real-world, production-ready AI workflows using MCP with LangChain, LangGraph, and CrewAI through fully practical, project-based implementations. <div align="center"> </div> <img width="1025" height="240" alt="image" src="https://github.com/user-attachments/assets/5ecbd43e-74e4-488c-9970-02b4f00f6794" /> --- <div align="center"> <img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&height=260&text=AGENTIC%20AND%20GEN%20AI%20AGENTS%20WITH%20MCP&fontSize=40&fontColor=ffffff&animation=fadeIn" width="100%"/> </div> --- 10 Python AI/ML librarie Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 5/18/2026.

Freshness

Last checked 5/18/2026

Best For

Build-Agentic-AI-and-Gen-AI-Agents-with-MCP 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 OPENCLEW, runtime-metrics, public facts pack

Claim this agent
Agent DossierGitHubSafety: 66/100

Build-Agentic-AI-and-Gen-AI-Agents-with-MCP

Model Context Protocol (MCP) Bootcamp offers a deep dive into MCP architecture and its role in the Agentic AI ecosystem. Learn to build real-world, production-ready AI workflows using MCP with LangChain, LangGraph, and CrewAI through fully practical, project-based implementations. <div align="center"> </div> <img width="1025" height="240" alt="image" src="https://github.com/user-attachments/assets/5ecbd43e-74e4-488c-9970-02b4f00f6794" /> --- <div align="center"> <img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&height=260&text=AGENTIC%20AND%20GEN%20AI%20AGENTS%20WITH%20MCP&fontSize=40&fontColor=ffffff&animation=fadeIn" width="100%"/> </div> --- 10 Python AI/ML librarie

OpenClawself-declared

Public facts

5

Change events

1

Artifacts

0

Freshness

May 18, 2026

Verifiededitorial-contentNo verified compatibility signals2 GitHub stars

Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 5/18/2026.

2 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

May 18, 2026

Vendor

Ratnesh 181998

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 5/18/2026.

Setup snapshot

git clone https://github.com/Ratnesh-181998/Build-Agentic-AI-and-Gen-AI-Agents-with-MCP.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    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.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Ratnesh 181998

profilemedium
Observed May 11, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed May 11, 2026Source linkProvenance
Adoption (1)

Adoption signal

2 GitHub stars

profilemedium
Observed May 11, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

0

Snippets

0

Languages

python

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Model Context Protocol (MCP) Bootcamp offers a deep dive into MCP architecture and its role in the Agentic AI ecosystem. Learn to build real-world, production-ready AI workflows using MCP with LangChain, LangGraph, and CrewAI through fully practical, project-based implementations. <div align="center"> </div> <img width="1025" height="240" alt="image" src="https://github.com/user-attachments/assets/5ecbd43e-74e4-488c-9970-02b4f00f6794" /> --- <div align="center"> <img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&height=260&text=AGENTIC%20AND%20GEN%20AI%20AGENTS%20WITH%20MCP&fontSize=40&fontColor=ffffff&animation=fadeIn" width="100%"/> </div> --- 10 Python AI/ML librarie

Full README
<div align="center">

AI Engineer

</div> <img width="1025" height="240" alt="image" src="https://github.com/user-attachments/assets/5ecbd43e-74e4-488c-9970-02b4f00f6794" />
<div align="center"> <img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&height=260&text=AGENTIC%20AND%20GEN%20AI%20AGENTS%20WITH%20MCP&fontSize=40&fontColor=ffffff&animation=fadeIn" width="100%"/> </div>

10 Python AI/ML libraries

<img width="595" height="727" alt="image" src="https://github.com/user-attachments/assets/616453ee-00a0-475c-b84c-b1c035e9a918" />

Build Agentic AI and Gen AI Agents with MCP

  • Model Context Protocol (MCP) Bootcamp offers a deep dive into MCP architecture and its role in the Agentic AI ecosystem. Learn to build real-world, production-ready AI workflows using MCP with LangChain, LangGraph, and CrewAI through fully practical, project-based implementations.
  • https://fastmcp.cloud/

Table of contents - Live Demo & Topics in Details Coming Soon

Section 1 Model Context Protocol

Section 2 Getting Started With Claude Desktop And Cursor IDE

Section 3 Cursor IDE MCP Server Setup

Section 4 How to build Your Own MCP Client using Python and Google Gemini API

Section 5 How to build Docker MCP Server

Section 6 LangChain MCP Client using LangChain MCP Adapters

Section 7 MCP Client with Multiple Server Support

Section 8 MCP Server and Client using SSE

Section 9 Deploying MCP Server to AWS Cloud Platform

Section 10 Real Time Weather Agent using MCP and MCP Inspector

Section 11 Real Time Job Recommendation System

Section 12 StoryForge Agent

Section 13 Clinisight AI

Section 14 Build Agent with Google Development Kit ADK


Model Context Protocol (MCP) โ€“ The USB-C for AI Applications

<img width="1121" height="1343" alt="image" src="https://github.com/user-attachments/assets/eae5ab87-7147-46a6-8f49-ad8be55a1c95" /> <img width="1069" height="1307" alt="image" src="https://github.com/user-attachments/assets/2f0ed634-5b3d-4c36-8ee0-4aa11834a7df" />

Just explored an incredible book on Model Context Protocol (MCP)

โ€” and honestly, it completely reshaped how I think about the future of Agentic AI.

  • For years, AI systems have been powerful individually, but fragmented when it comes to collaboration, context-sharing, scalability, and orchestration.

  • MCP changes that.

  • This book explains how MCP is becoming the foundational communication layer for next-generation AI ecosystems โ€” enabling AI agents, tools, servers, and workflows to operate with shared context, adaptive intelligence, modularity, and secure multi-agent coordination.

Why MCP matters for the future of AI:

<img width="1054" height="1048" alt="image" src="https://github.com/user-attachments/assets/f32597dd-e030-4eab-a745-810228bfb57b" /> <img width="1074" height="1006" alt="image" src="https://github.com/user-attachments/assets/f65a3426-c364-4931-9522-5b934d4c5309" />
<img src="https://capsule-render.vercel.app/api?type=rect&color=gradient&customColorList=24,20,12,6&height=3" width="100%">

๐Ÿ“œ License

License

Licensed under the MIT License - Feel free to fork and build upon this innovation! ๐Ÿš€


๐Ÿ“ž CONTACT & NETWORKING ๐Ÿ“ž

๐Ÿ’ผ Professional Networks

LinkedIn GitHub X Portfolio Email Medium Stack Overflow

๐Ÿš€ AI/ML & Data Science AI/ML 1620+ Problem Solved

Streamlit HuggingFace Kaggle

๐Ÿ’ป Competitive Programming Including all coding plateform's 5000+ Problems/Questions solved

LeetCode HackerRank CodeChef Codeforces GeeksforGeeks HackerEarth InterviewBit


๐Ÿ“Š GitHub Stats & Metrics ๐Ÿ“Š

Profile Views

<img src="https://streak-stats.demolab.com?user=Ratnesh-181998&theme=radical&hide_border=true&background=0D1117&stroke=4ECDC4&ring=F38181&fire=FF6B6B&currStreakLabel=4ECDC4" alt="GitHub Streak Stats" width="48%"/>

<img src="https://github-readme-activity-graph.vercel.app/graph?username=Ratnesh-181998&theme=react-dark&hide_border=true&bg_color=0D1117&color=4ECDC4&line=F38181&point=FF6B6B" width="48%" />
<img src="https://readme-typing-svg.herokuapp.com?font=Fira+Code&size=24&duration=3000&pause=1000&color=4ECDC4&center=true&vCenter=true&width=600&lines=Ratnesh+Kumar+Singh;Data+Scientist+%7C+AI%2FML+Engineer;4%2B+Years+Building+Production+AI+Systems" alt="Typing SVG" /> <img src="https://readme-typing-svg.herokuapp.com?font=Fira+Code&size=18&duration=2000&pause=1000&color=F38181&center=true&vCenter=true&width=600&lines=Built+with+passion+for+the+AI+Community+๐Ÿš€;Innovating+the+Future+of+AI+%26+ML;MLOps+%7C+LLMOps+%7C+AIOps+%7C+GenAI+%7C+AgenticAI+Excellence" alt="Footer Typing SVG" /> <img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&customColorList=6,11,20&height=120&section=footer" width="100%">

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/contract"
curl -s "https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

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

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation โ€ข (~400 MCP servers for AI agents) โ€ข AI Automation / AI Agent with MCPs โ€ข AI Workflows & AI Agents โ€ข MCPs for AI Agents

OPENCLAW
Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.

MCPOPENCLAW
Github ReposUpdated 6mo agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | ๐ŸŒŸ Star if you like it!

MCPOPENCLAW
Github ReposUpdated 7mo agoRank 70

CopilotKit

The Frontend for Agents & Generative UI. React + Angular

OPENCLAW
Machine Appendix

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-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-10-09T01:59:19.100Z"
    }
  },
  "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",
    "label": "Vendor",
    "value": "Ratnesh 181998",
    "category": "vendor",
    "href": "https://github.com/Ratnesh-181998/Build-Agentic-AI-and-Gen-AI-Agents-with-MCP",
    "sourceUrl": "https://github.com/Ratnesh-181998/Build-Agentic-AI-and-Gen-AI-Agents-with-MCP",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-05-11T06:22:36.186Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "protocols",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "category": "compatibility",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-05-11T06:22:36.186Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "traction",
    "label": "Adoption signal",
    "value": "2 GitHub stars",
    "category": "adoption",
    "href": "https://github.com/Ratnesh-181998/Build-Agentic-AI-and-Gen-AI-Agents-with-MCP",
    "sourceUrl": "https://github.com/Ratnesh-181998/Build-Agentic-AI-and-Gen-AI-Agents-with-MCP",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-05-11T06:22:36.186Z",
    "isPublic": true,
    "metadata": {}
  },
  {
    "factKey": "docs_crawl",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "category": "integration",
    "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,
    "metadata": {}
  },
  {
    "factKey": "handshake_status",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "category": "security",
    "href": "https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/crewai-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-m/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true,
    "metadata": {}
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub ยท 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,
    "metadata": {}
  }
]

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