fastapi_mcp
★ 12.0k
vs
coder_eval
★ 154
fastapi_mcp vs coder_eval
fastapi_mcp: FastAPI-MCP allows you to expose your existing FastAPI endpoints as Model Context Protocol (MCP) tools. It offers native integration with FastAPI, including built-in authentication using existing dependencies, and preserves schemas and documentation.; coder_eval: Coder Eval runs a real coding agent (Claude Code, Codex, Antigravity, OpenCode or Pi) in a sandbox against declarative YAML tasks and scores the files and commands it produced. It supports weighted 0.0-1.0 criteria, skill-trigger checks, A/B experiments and cost telemetry, and can gate CI on agent quality.
01
TL;DR
fastapi_mcpDev Tooling · ★ 12.0k
When to choose:
- You already have a FastAPI application and want to expose its endpoints as MCP tools while reusing your existing FastAPI authentication dependencies and Swagger schemas.
- You want to mount the MCP server directly onto your ASGI app or deploy it separately under an MIT license.
When to skip:
- You are building a standalone MCP server from scratch rather than wrapping a FastAPI app; use FastMCP or the official MCP Python SDK.
- You need an actively updated repository (last push was November 2025).
coder_evalDev Tooling · ★ 154
Benchmark coding agents on your own domain tasks
02
Side-by-Side Comparison
Field
fastapi_mcpcoder_evalCategory
Dev Tooling
Dev Tooling
Stars
★ 12.0k
★ 154
License
MIT
Apache-2.0
Install Command
uv add fastapi-mcp
uv tool install coder-eval
Updated
11mo ago
1d ago
Open Source
Yes
Yes
Tags
FastAPI, MCP, Python
agent-evaluation, agent-skills, agent-testing
03
Features
fastapi_mcp01Authentication built in, using your existing FastAPI dependencies!
02FastAPI-native: Not just another OpenAPI -> MCP converter
03Zero/Minimal configuration required
04Preserving schemas of your request models and response models
05Flexible deployment - Mount your MCP server to the same app, or deploy separately
coder_eval01Declarative YAML tasks with pinned dependencies and success criteria
02Sandboxed execution with resource limits
03Weighted 0.0-1.0 scoring, including LLM-graded rubrics and skill_triggered checks
04A/B experiments across agents, models, tools and prompts
05Telemetry for every tool call, token count and cost
04
Use Cases
fastapi_mcp↳Integrating FastAPI services as tools for large language models (LLMs) that support MCP.
↳Enabling LLMs to interact with and utilize existing business logic and data exposed via FastAPI.
↳Quickly exposing authenticated FastAPI APIs as discoverable and usable tools within an MCP ecosystem.
coder_eval↳Benchmark coding agents on your own domain tasks
↳Verify that a skill actually triggers in the agent you ship for
↳Fail CI builds when agent or skill quality regresses
05
Best For
fastapi_mcpMost PopularEssential
coder_eval—
FAQ
FAQ
What is the difference between fastapi_mcp and coder_eval?
Both fastapi_mcp and coder_eval are in the Dev Tooling category. fastapi_mcp has 12.0k stars, while coder_eval has 154 stars.
Which is better, fastapi_mcp or coder_eval?
The best choice depends on your use case. Choose fastapi_mcp if Integrating FastAPI services as tools for large language models (LLMs) that support MCP., and coder_eval if Benchmark coding agents on your own domain tasks.
Is fastapi_mcp free or open source?
Yes, fastapi_mcp is open source on GitHub (MIT).
Is coder_eval free or open source?
Yes, coder_eval is open source on GitHub (Apache-2.0).
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