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.
Ask an LLM agent:
Install FastContext Agent Tools from
https://github.com/Jakevin/fastcontext-agent-tools; its package installation includes Microsoft FastContext. Configurepython -m fastcontext_mcpas a stdio MCP server withBASE_URL,MODEL,API_KEY, andFASTCONTEXT_ALLOWED_ROOTS, then enableskills/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"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
<final_answer> 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: https://github.com/microsoft/fastcontext
- Model card: https://huggingface.co/microsoft/FastContext-1.0-4B-SFT
- Paper: https://arxiv.org/abs/2606.14066
git clone https://github.com/Jakevin/fastcontext-agent-tools
cd fastcontext-agent-tools
python -m pip install -e .
python -m fastcontext_mcp --print-healthIf your Python scripts directory is on PATH, fastcontext-mcp --print-health
works too.
- 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"FASTCONTEXT_ALLOWED_ROOTS is an os.pathsep separated allowlist. If unset,
the MCP server only allows repositories under the directory where the server was
started.
Example stdio config:
{
"mcpServers": {
"fastcontext": {
"command": "python",
"args": ["-m", "fastcontext_mcp"],
"env": {
"BASE_URL": "http://127.0.0.1:30000/v1",
"MODEL": "microsoft/FastContext-1.0-4B-SFT",
"API_KEY": "your-api-key",
"FASTCONTEXT_ALLOWED_ROOTS": "/path/to/repos"
}
}
}
}Localized MCP guides:
- Traditional Chinese: docs/mcp.zh-TW.md
- Japanese: docs/mcp.ja.md
Checks whether the bundled fastcontext.cli module is importable and whether
the endpoint environment is set.
Runs FastContext against a repository and returns parsed citations plus raw output.
{
"repo_path": "/path/to/repo",
"query": "Locate the request validation logic for uploaded files",
"max_turns": 6,
"citation": true,
"timeout_seconds": 300
}Same as fastcontext_explore, but saves a FastContext JSONL trajectory. Relative
trajectory_path values are resolved inside repo_path.
The bundled skill lives at:
skills/fastcontext-explorer
Install by copying or symlinking that folder into your Codex skills directory:
mkdir -p "${CODEX_HOME:-$HOME/.codex}/skills"
ln -s "$(pwd)/skills/fastcontext-explorer" "${CODEX_HOME:-$HOME/.codex}/skills/fastcontext-explorer"Use the skill when a coding task requires repository localization before editing. FastContext citations are candidate evidence; the main agent should still read the cited files before changing code.
Additional project report:
- Full report: docs/REPORT.md
Run tests:
PYTHONPATH=src python -m unittest discover -s testsValidate the bundled Codex skill:
python /path/to/skill-creator/scripts/quick_validate.py skills/fastcontext-explorer- The MCP server exposes no edit/write tools.
repo_pathmust resolve underFASTCONTEXT_ALLOWED_ROOTS.- Secrets are read from environment variables only.
- Trajectories are written only when requested.
MIT