Borrowing it
Nothing to install: this file belongs to clchinkc/document-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/clchinkc/document-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/clchinkc/document-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/clchinkc/document-mcp/agents-md)<a href="https://agentmods.dev/instructions/clchinkc/document-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/clchinkc/document-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/clchinkc/document-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/clchinkc/document-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 | $0.02390 | $0.02390 |
| Opus 5.5 | $0.00956 | $0.00956 |
| Sonnet 5.5 | $0.00478 | $0.00478 |
| Haiku 4.5 | $0.00239 | $0.00239 |
Grade A, and why
document-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 2mo 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 — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Usage Guide
The Document MCP system includes two AI agents that demonstrate how to use the MCP tools effectively. These agents are separate from the core MCP package and run directly from source code.
Latest Updates (v0.0.3)
- ✅ Pagination Support: All agents now work with the new pagination system for large documents
- ✅ GCP Observability: All tool calls now traced with logs/metrics (works locally too)
- ✅ OpenRouter Support: Use OpenRouter models with priority over OpenAI and Gemini
- ✅ Tool Selection Benchmarks: Evaluation framework for measuring agent tool selection accuracy
- ✅ Enhanced Testing: Complete test coverage with 536 tests passing (61% coverage)
- ✅ Improved Error Handling: Better timeout management for E2E scenarios
Prerequisites
-
Install the MCP package (for the core tools):
pip install document-mcp -
Clone the repository (for the agents):
git clone https://github.com/your-org/document-mcp.git cd document-mcp -
Install agent dependencies:
uv sync --dev # or pip install -r requirements-agents.txt -
Set up API keys (choose one, priority order: OpenRouter > OpenAI > Gemini):
# For OpenRouter (recommended - access to multiple models) export OPENROUTER_API_KEY="your-openrouter-key" # For OpenAI export OPENAI_API_KEY="your-openai-key" # For Google Gemini export GEMINI_API_KEY="your-gemini-key"Or create a
.envfile in the project root (see.env.example).
Agent Types
Simple Agent
Best for: Quick operations, single-step tasks, structured JSON output
# Basic usage
uv run python src/agents/simple_agent/main.py --query "list all documents"
# With specific model
uv run python src/agents/simple_agent/main.py --query "create document 'Meeting Notes'" --model "gemini-2.5-flash"
# Interactive mode
uv run python src/agents/simple_agent/main.py --interactive
# Check configuration
uv run python src/agents/simple_agent/main.py --check-config
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.
- 2mo ago First seen · 351 lines · 2,390 tokens per session scan A 4cf8222ff171
document-mcp AGENTS.md is an instructions file published in the GitHub repository clchinkc/document-mcp (0 stars, last pushed 5mo ago), licensed MIT. It adds 2,390 tokens to every session, about $0.0096 per session on Opus 5.5. 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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