MCP 서버 및 Codex 기술은 Microsoft의 QuickContext를 읽기 전용으로 사용합니다. 저장소 탐험 subagent.

FastContext는 코딩 대리인을 위한 1개의 좁은 질문을 대답합니다:

어떤 파일 및 선 범위는 주요 대리인이 이 업무를 해결하기 전에 검사해야 합니까?

이 저장소는 완전한 통합을 제공합니다:

• fastcontext-mcp: Microsoft FastContext를 Pinned runtime Dependency로 설치하는 Python stdio MCP 서버.
• skills/fastcontext-explorer: 저장소 탐험을 거부할 때 에이전트를 가르치는 Codex 기술.
• 영어, 중국어, 일본어로 MCP 설정 가이드

그것은 뭉치 모형 무게, 런 inference, 또는 저장소를 수정하지 않습니다. MCP 소개 서버는 같은 Python 환경에서 번들 fastcontext.cli 모듈을 실행합니다. 주요 에이전트에 대한 후보 파일 라인 인용을 반환합니다.

원라인 LLM 에이전트 설치 Prompt

LLM 대리인에게:

https://github.com/Jakevin/fastcontext-agent-tools에서 FastContext Agent Tools 설치; 패키지 설치에는 Microsoft FastContext가 포함되어 있습니다.

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"