Borrowing it
Nothing to install: this file belongs to yumeiriowl/repo-graphrag-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/yumeiriowl/repo-graphrag-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/yumeiriowl/repo-graphrag-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/yumeiriowl/repo-graphrag-mcp/agents-md)<a href="https://agentmods.dev/instructions/yumeiriowl/repo-graphrag-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/yumeiriowl/repo-graphrag-mcp/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/yumeiriowl/repo-graphrag-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/yumeiriowl/repo-graphrag-mcp/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01315 | $0.01315 |
| Opus 5 | $0.00658 | $0.00658 |
| Sonnet 5 | $0.00263 | $0.00263 |
| Haiku 4.5 | $0.00131 | $0.00131 |
Grade A, and why
repo-graphrag-mcp AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repo GraphRAG MCP Usage Guide
"Repo GraphRAG MCP" extracts entities (classes, functions, etc.) and relationships from repository code and documentation to build a knowledge graph. Vectorizes and indexes all text. Combines graph search and vector search to answer questions and generate implementation plans with understanding of code structure.
Prerequisites
- Python 3.11 or higher
- uv package manager
- Install dependencies:
cd repo-graphrag-mcp
uv sync
- Configure environment variables:
Copy
.env.exampleto create a.envfile
Note: Assumes users have already set up their environment. Refer to repo-graphrag-mcp/.env.example only when MCP startup or operation errors occur.
Three Tools
graph_create- Analyze repository to build/update knowledge graph and vector indexgraph_query- Answer questions about the repository using the knowledge graphgraph_plan- Generate implementation plans with understanding of existing code structure
All tools are invoked with the graph: prefix in user requests.
Tool 1: graph_create
Purpose: Analyze a directory to build a knowledge graph and vector index.
Parameters:
read_dir_path(required): Absolute path to the directory to analyzestorage_name(optional): Name of the storage (default: "storage")
Usage Examples:
graph: /home/user/myproject my_project
graph: C:\projects\webapp webapp_storage
graph: /path/to/repo # Uses default storage name "storage"
Behavior:
- First run: Processes all files and creates storage
- Subsequent runs: Processes only changed/new/deleted files (incremental update)
- Storage is created relative to the MCP server directory
Processed File Types:
Code files are fixed. Other types can be modified in .env.
- Code: .py, .cpp, .h, .java, .rs, .c, .cs, .go, .rb, .js, .jsx, .kt, .kts, .ts, .tsx, .html, .htm, .css
- Documents (default): .txt, .md, .rst, and special files: readme, changelog (case insensitive)
- Excluded (default): pycache, .git, .github, .venv, node_modules, .DS_Store, Thumbs.db, robots.txt, bac, backup, temp, tmp
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 163 lines · 1,315 tokens per session scan A 2cf2e0519caa
repo-graphrag-mcp AGENTS.md is an instructions file published in the GitHub repository yumeiriowl/repo-graphrag-mcp (7 stars, last pushed 7mo ago), licensed MIT. It adds 1,315 tokens to every session, about $0.0066 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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