MCP服务器和Codex技能，用于将Microsoft的FastContext用作只读 仓库探索子代理。

FastContext 回答了一个编码代理的一个狭窄问题：

主代理在解决此任务前应检查哪些文件和行范围？

该仓库提供完整的集成：

• fastcontext-mcp：一台 Python 标准 MCP 服务器，安装 Microsoft FastContext 作为钉顶运行时依赖。
• skills/fastcontext-explorer：一个教导特工何时委托仓库探索的法典技能。
• MCP设置指南，提供英文、繁体中文和日文。

它不捆绑模型权重、运行推理或修改存储库。MCP 服务器在同一Python环境中运行捆绑的fastcontext.cli模块 并返回候选文件行引用，供主代理核实。

一行LLM代理安装提示

向LLM代理咨询：

从 https://github.com/Jakevin/fastcontext-agent-tools 安装 FastContext 代理工具;其软件包安装包含Microsoft FastContext。

FastContext Agent Tools

MCP server and Codex skill for using Microsoft’s FastContext as a read-only repository exploration subagent.

FastContext answers one narrow question for a coding agent:

Which files and line ranges should the main agent inspect before solving this task?

This repository provides the complete integration:

• fastcontext-mcp: a Python stdio MCP server that installs Microsoft FastContext as a pinned runtime dependency.
• skills/fastcontext-explorer: a Codex skill that teaches an agent when to delegate repository exploration.
• MCP setup guides in English, Traditional Chinese, and Japanese.

It does not bundle model weights, run inference, or modify repositories. The MCP server runs the bundled fastcontext.cli module in the same Python environment and returns candidate file-line citations for the main agent to verify.

One-Line LLM Agent Install Prompt

Ask an LLM agent:

Install FastContext Agent Tools from https://github.com/Jakevin/fastcontext-agent-tools; its package installation includes Microsoft FastContext. Configure python -m fastcontext_mcp as a stdio MCP server with BASE_URL, MODEL, API_KEY, and FASTCONTEXT_ALLOWED_ROOTS, then enable skills/fastcontext-explorer.

Direct install command for Codex-style local skills:

git clone https://github.com/Jakevin/fastcontext-agent-tools && cd fastcontext-agent-tools && python -m pip install -e . && mkdir -p "${CODEX_HOME:-$HOME/.codex}/skills" && ln -sfn "$(pwd)/skills/fastcontext-explorer" "${CODEX_HOME:-$HOME/.codex}/skills/fastcontext-explorer"

Why This Exists

Microsoft FastContext separates repository exploration from code solving. The upstream project describes a dedicated explorer that uses read-only READ, GLOB, and GREP tools, issues parallel tool calls, and returns compact `` citations. Microsoft reports Mini-SWE-Agent integration gains of up to 5.5 score improvement and up to 60% main-agent token reduction.

Primary sources:

• Microsoft FastContext:
• Model card:
• Paper:

Quick Install

git clone https://github.com/Jakevin/fastcontext-agent-tools
cd fastcontext-agent-tools
python -m pip install -e .
python -m fastcontext_mcp --print-health

If your Python scripts directory is on PATH, fastcontext-mcp --print-health works too.

Requirements

• Python 3.12+.
• An OpenAI-compatible endpoint serving a FastContext-compatible model.

Installing this package also installs Microsoft FastContext from the pinned official source revision. No separate FastContext checkout or CLI installation is required.

Endpoint environment:

export BASE_URL="http://127.0.0.1:30000/v1"
export MODEL="microsoft/FastContext-1.0-4B-SFT"
export API_KEY="your-api-key"
export FASTCONTEXT_ALLOWED_ROOTS="/path/to/repos"