{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_4p3jn7fgstme","handle":"iflow-mcp-adam-paterson-mcp-crew-ai","url":"https://wellknown.network/agents/iflow-mcp-adam-paterson-mcp-crew-ai","links":{"self":"https://wellknown.network/agents/iflow-mcp-adam-paterson-mcp-crew-ai/record.json","html":"https://wellknown.network/agents/iflow-mcp-adam-paterson-mcp-crew-ai","markdown":"https://wellknown.network/agents/iflow-mcp-adam-paterson-mcp-crew-ai/record.md","api":"https://wellknown.network/api/v1/agents/iflow-mcp-adam-paterson-mcp-crew-ai","status":"https://wellknown.network/api/v1/agents/iflow-mcp-adam-paterson-mcp-crew-ai/status","claim":"https://wellknown.network/agents/iflow-mcp-adam-paterson-mcp-crew-ai/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/iflow-mcp-adam-paterson-mcp-crew-ai/claim.json","badge":"https://wellknown.network/agents/iflow-mcp-adam-paterson-mcp-crew-ai/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/iflow-mcp-adam-paterson-mcp-crew-ai/history","tools":"https://wellknown.network/api/v1/agents/iflow-mcp-adam-paterson-mcp-crew-ai/tools"},"ard":{"identifier":"urn:air::server:iflow-mcp-adam-paterson-mcp-crew-ai","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp_adam-paterson-mcp-crew-ai","summary":"MCP Crew AI Server - Run CrewAI agents through Model Context Protocol","description":"<div align=\"center\">\n  <img src=\"https://github.com/crewAIInc/crewAI/blob/main/docs/crewai_logo.png\" alt=\"CrewAI Logo\" />\n</div>\n\n# MCP Crew AI Server\n\nMCP Crew AI Server is a lightweight Python-based server designed to run, manage and create CrewAI workflows. This project leverages the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) to communicate with Large Language Models (LLMs) and tools such as Claude Desktop or Cursor IDE, allowing you to orchestrate multi-agent workflows with ease.\n\n## Features\n\n- **Automatic Configuration:** Automatically loads agent and task configurations from two YAML files (`agents.yml` and `tasks.yml`), so you don't need to write custom code for basic setups.\n- **Command Line Flexibility:** Pass custom paths to your configuration files via command line arguments (`--agents` and `--tasks`).\n- **Seamless Workflow Execution:** Easily run pre-configured workflows through the MCP `run_workflow` tool.\n- **Local Development:** Run the server locally in STDIO mode, making it ideal for development and testing.\n\n## Installation\n\nThere are several ways to install the MCP Crew AI server:\n\n### Option 1: Install from PyPI (Recommended)\n\n```bash\npip install mcp-crew-ai\n```\n\n### Option 2: Install from GitHub\n\n```bash\npip install git+https://github.com/adam-paterson/mcp-crew-ai.git\n```\n\n### Option 3: Clone and Install\n\n```bash\ngit clone https://github.com/adam-paterson/mcp-crew-ai.git\ncd mcp-crew-ai\npip install -e .\n```\n\n### Requirements\n\n- Python 3.11+\n- MCP SDK\n- CrewAI\n- PyYAML\n\n## Configuration\n\n- **agents.yml:** Define your agents with roles, goals, and backstories.\n- **tasks.yml:** Define tasks with descriptions, expected outputs, and assign them to agents.\n\n**Example `agents.yml`:**\n\n```yaml\nzookeeper:\n  role: Zookeeper\n  goal: Manage zoo operations\n  backstory: >\n    You are a seasoned zookeeper with a passion for wildlife conservation...\n```\n\n**Example `tasks.yml`:**\n\n```yaml\nwrite_stories:\n  description: >\n    Wri…","publisher":null,"homepage":"https://github.com/adam-paterson/mcp-crew-ai","repository":"https://github.com/adam-paterson/mcp-crew-ai","version":"0.1.0","license":null,"protocols":["mcp"],"tags":["mcp"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp_adam-paterson-mcp-crew-ai","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi"}},"derived":{"capabilities":[{"slug":"automation.orchestration","name":"Agent Orchestration","confidence":1,"provenance":"derived"},{"slug":"dev.terminal","name":"Terminal & Shell","confidence":0.825,"provenance":"derived"},{"slug":"dev.version-control","name":"Version Control","confidence":0.745,"provenance":"derived"}],"categories":["automation","dev"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"iflow-mcp_adam-paterson-mcp-crew-ai","registry":"pypi","observedAt":"2026-10-28T03:24:07.256Z","publishedAt":"2026-02-14T08:17:39.273243Z","latestVersion":"0.1.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp_adam-paterson-mcp-crew-ai","url":"https://pypi.org/project/iflow-mcp_adam-paterson-mcp-crew-ai/","firstSeenAt":"2026-09-09T17:22:10.219Z","fetchedAt":"2026-10-28T03:22:41.359Z","normalizedAt":"2026-10-28T03:22:41.359Z"}]},"firstSeenAt":"2026-09-09T17:22:10.219Z","updatedAt":"2026-10-28T03:24:07.256Z"}