What is documentdb-mcp AGENTS.md?

Project instructions for a Python service that connects an AI agent to tools and external APIs through an MCP server. MCP is a standard way for an AI application to call outside tools.

Use it when modifying the server, agent, modular skills, API client, or tool integrations in the documentdb-mcp project.

It gives contributors a shared description of the architecture, workflow, technology choices, and required commands.

documentdb-mcp AGENTS.md — Instructions file by Knuckles-Team

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add instructions/knuckles-team/documentdb-mcp/agents-md

Clone the repo

git clone --depth 1 https://github.com/Knuckles-Team/documentdb-mcp

Made for: Codex, OpenCode.

Per session 4,038 This file is loaded in full into every session.

When invoked 4,038 The same file — it is already loaded in full.

Security scan A 0 findings. Scan, not verified.

Origin 92% copy Near-identical to another mod in the catalogue.

Token cost

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	$0.04038	$0.04038
Opus 5	$0.02019	$0.02019
Sonnet 5	$0.00808	$0.00808
Haiku 4.5	$0.00404	$0.00404

Measured 2d ago against content hash d95e292ecc7f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

documentdb-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 2d 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.

Origin

This is a copy

92% identical to servicenow-api AGENTS.md — 15 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

AGENTS.md · 326 lines

How it starts

The opening of the file, as written. The whole thing — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Claude Code loads this file via CLAUDE.md (@AGENTS.md import) — the two stay in sync. Edit this file, not CLAUDE.md.

Tech Stack & Architecture

Language/Version: Python 3.10+
Core Libraries: agent-utilities, fastmcp, pydantic-ai
Key principles: Functional patterns, Pydantic for data validation, asynchronous tool execution.
Architecture:
- mcp_server.py: Main MCP server entry point and tool registration.
- agent_server.py: Pydantic AI agent definition and logic.
- skills/: Directory containing modular agent skills (if applicable).

Architecture Diagram

graph TD
    User([User/A2A]) --> Server[A2A Server / FastAPI]
    Server --> Agent[Pydantic AI Agent]
    Agent --> Skills[Modular Skills]
    Agent --> MCP[MCP Server / FastMCP]
    MCP --> Client[API Client / Wrapper]
    Client --> ExternalAPI([External Service API])

Workflow Diagram

sequenceDiagram
    participant U as User
    participant S as Server
    participant A as Agent
    participant T as MCP Tool
    participant API as External API

    U->>S: Request
    S->>A: Process Query
    A->>T: Invoke Tool
    T->>API: API Request
    API-->>T: API Response
    T-->>A: Tool Result
    A-->>S: Final Response
    S-->>U: Output

Commands (run these exactly)

Installation

pip install .[all]

Quality & Linting (run from project root)

pre-commit run --all-files

Execution Commands

documentdb-mcp\ndocumentdb_mcp.mcp:mcp_server\n# documentdb-agent\ndocumentdb_mcp.agent:agent_server

Project Structure Quick Reference

MCP Entry Point → mcp_server.py
Agent Entry Point → agent_server.py
Source Code → documentdb_mcp/
Skills → skills/ (if exists)

File Tree

├── .bumpversion.cfg\n├── .dockerignore\n├── .env\n├── .gitattributes\n├── .github\n│   └── workflows\n│       └── pipeline.yml\n├── .gitignore\n├── .pre-commit-config.yaml\n├── AGENTS.md\n├── Dockerfile\n├── LICENSE\n├── MANIFEST.in\n├── README.md\n├── compose.yml\n├── debug.Dockerfile\n├── documentdb_mcp\n│   ├── __init__.py\n│   ├── __main__.py\n│   ├── agent_server.py\n│   └── mcp_server.py\n├── mcp.compose.yml\n├── pyproject.toml\n├── pytest.ini\n└── requirements.txt

Read the full file on GitHub · 326 lines

Changes

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.

2d ago First seen · 326 lines · 4,038 tokens per session scan A d95e292ecc7f

Subscribe to this mod's changes

documentdb-mcp AGENTS.md is an instructions file published in the GitHub repository Knuckles-Team/documentdb-mcp (2 stars, last pushed 4d ago), licensed MIT. It adds 4,038 tokens to every session, about $0.0202 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to servicenow-api AGENTS.md, differing in 15 lines, and is treated as a copy.

a2a a2a-server ag-ui documentdb mcp-server

documentdb-mcp AGENTS.md