fegis
Define AI tools in YAML with natural language schemas. All tool usage is automatically stored in Qdrant vector database, enabling semantic search, filtering, and memory retrieval across sessions.
No README could be loaded. View the project on GitHub for full documentation.
Frequently asked questions
What is fegis?
fegis is Define AI tools in YAML with natural language schemas. All tool usage is automatically stored in Qdrant vector database, enabling semantic search, filtering, and memory retrieval across sessions.
How do I install fegis?
Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.
Is fegis open source?
Yes — it is hosted on GitHub at https://github.com/p-funk/FEGIS and has 21 stars.
Related MCP tools
fastapi_mcpExpose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth! Python-based implementation. Trusted by 11000+ developers.
mcp-bridgeA middleware to provide an openAI compatible endpoint that can call MCP tools Python-based implementation. Trusted by 800+ developers.
wcgwShell and coding agent on claude desktop app for the Model Context Protocol. Enhance AI assistants with powerful integrations. Python-based implementation.
linkedin-mcp-serverThis MCP server allows Claude and other AI assistants to access your LinkedIn. Scrape LinkedIn profiles and companies, get your recommended jobs, and perform...
gpt-researcherAn LLM agent that conducts deep research (local and web) on any given topic and generates a long report with citations. Built for the Model Context Protocol to
fastmcp🚀 The fast, Pythonic way to build MCP servers and clients Trusted by 19900+ developers. Trusted by 19900+ developers. Trusted by 19900+ developers.
Run your own MCP server? See who uses it and what to fix.
Measure it with TrackMCP