Advertise
MCP.so
Sign In

MyAIServ: AI-Powered FastAPI Server with MCP Server

@eagurin

Repository

Basic information

Category

Developer Tools

License

MIT

Transports

stdio

Author

eagurin

About MyAIServ: AI-Powered FastAPI Server with MCP Server

High-performance FastAPI server implementing Model Context Protocol (MCP) for seamless integration with Large Language Models (LLMs). Built with modern stack: FastAPI, Elasticsearch, Redis, Prometheus, and Grafana.

#myaiserv#fastapi#ai-server

MyAIServ: AI-Powered FastAPI Server with MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "myaiserv": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

MyAIServ: AI-Powered FastAPI Server with MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MyAIServ: AI-Powered FastAPI Server with MCP 🚀?

MyAIServ is a FastAPI implementation of the Model Context Protocol (MCP), providing a standardized interface for interaction between LLM models and applications. It is intended for developers who need a high-performance, extensible API that bridges LLMs with tools, resources, and real-time communication.

How to use MyAIServ: AI-Powered FastAPI Server with MCP 🚀?

Clone the repository, install Poetry, then run poetry install to set up dependencies. Start the server with poetry run uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload or via the just run command. The API is then accessible at http://localhost:8000, with Swagger UI at /docs, ReDoc at /redoc, and GraphQL Playground at /graphql.

Key features of MyAIServ: AI-Powered FastAPI Server with MCP 🚀

  • High-performance API built on FastAPI with async operations
  • Full MCP support for resources, tools, prompts, and sampling
  • Prometheus/Grafana monitoring with metrics at /metrics
  • Extensible via simple interfaces for new tools
  • GraphQL API for flexible data queries
  • WebSocket support for real-time interactions
  • Semantic search integration with Elasticsearch
  • Redis caching for improved performance

Use cases of MyAIServ: AI-Powered FastAPI Server with MCP 🚀

  • Providing LLMs with standardized access to tools like file operations, weather, text analysis, and image processing
  • Real-time data exchange between applications and LLMs via WebSocket
  • Flexible data querying and mutation using GraphQL
  • Monitoring API usage and performance metrics in production

Frequently asked questions

1

What are the runtime dependencies?

Python 3.9+ and Poetry are required. Redis and Elasticsearch are optional but recommended for caching and semantic search.

2

How do I run tests?

Tests can be run using `poetry run pytest` or `just test`.

3

Does the server support Docker?

Yes, the project includes a `docker-compose.yml` for containerized deployment. You can run all services with `docker compose up -d`.

4

How can I integrate this with an LLM?

Retrieve available tools via GET `/tools`, then include those tools in your LLM API request (e.g., using `tools` and `tool_choice: "auto"` in the chat completion call).

5

What metrics are exposed?

Prometheus metrics are available at `/metrics`, including request counts per tool, execution times, and error counts.

Comments

More Developer Tools MCP servers

JiCo for Jira & Confluence – PII-redacting MCP server with Human-in-the-Loop

drkv-com

JiCo for Jira & Confluence: local MCP server for Jira Data Center - redacts personal data before the AI model, holds every write for approval

Moxie Docs

Jackalope-Dev

Automated codebase documentation for GitHub: searchable docs, MCP context for AI agents, doc drift detection, and Friday Cleanup PRs.

1

DocuWriter.ai

DocuWriter.ai

DocuWriter is an AI-powered platform for creating, updating and managing complete, structured documentation for entire codebases. Teams can connect repositories and generate documentation covering architecture, modules,

GripForge

gripforgeai

The tools your AI needs to make your games. Turn prompts into production-ready game assets — animated characters with their weapons attached, seamless textures, terrain, VFX, HUDs — and playable game kits Unity, Godot, U

1

FARPY

mangomunchr

Verified distributed compute for humans, applications, and agents. Submit Blender, Octane, and video workloads, route them across qualified GPUs, track asynchronous execution, download finished artifacts, and verify FARP

1
Advertise