Azure/gpt-rag-mcp is a Python server that exposes GPT-RAG capabilities through the Model Context Protocol. It is deployed with Azure resources and consumed by GPT-RAG through its MCP strategy, while the catalogue provides instructions, skills, and agents for operating it.
Borrowing it
Nothing to install: this file belongs to Azure/gpt-rag-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/Azure/gpt-rag-mcp/main/AGENTS.mdgit clone --depth 1 https://github.com/Azure/gpt-rag-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/azure/gpt-rag-mcp/agents-md)<a href="https://agentmods.dev/instructions/azure/gpt-rag-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/azure/gpt-rag-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/azure/gpt-rag-mcp/agents-md"><img src="https://agentmods.dev/badge/instructions/azure/gpt-rag-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 | $0.01862 | $0.01862 |
| Opus 5.5 | $0.00745 | $0.00745 |
| Sonnet 5.5 | $0.00372 | $0.00372 |
| Haiku 4.5 | $0.00186 | $0.00186 |
Grade A, and why
gpt-rag-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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GPT-RAG MCP engineering-agent contract
This is the stable repository-wide contract for GitHub Copilot engineering
agents. Detailed procedures live in .github/skills/; path-specific rules
live in .github/instructions/.
The agents and skills under .github/ help people develop, review, release,
and operate this repository. They are not the MCP server capabilities exposed
at runtime. Runtime tools, resources, and prompts live under src/tools/,
src/resources/, and src/prompts/ and are registered by src/server.py.
Priority
Follow, in order:
- Security, privacy, authorization, and platform instructions.
- Task requirements and acceptance criteria.
- Executable configuration and runtime contracts in this repository.
.github/copilot-instructions.md, this contract, and applicable scoped instructions.- Local conventions in the affected code.
Do not guess behavior that could affect MCP contracts, data, identity, security, deployment, releases, or production. Record the uncertainty and obtain a human decision.
What this repository is
Azure/gpt-rag-mcp is the Python 3.12 Model Context Protocol server consumed
by GPT-RAG through the orchestrator's mcp strategy. It is managed with uv
and uses FastMCP with Starlette to expose streamable HTTP endpoints. The
current source and dependency lock are authoritative; do not describe legacy
AutoGen or Semantic Kernel runtime variants as current behavior.
The repository is a runtime component of the multi-repository GPT-RAG
solution. Infrastructure is owned by Azure/GPT-RAG; azd provision and
azd up are intentionally blocked here. This repository builds and deploys
the MCP container into infrastructure provisioned by the platform repository.
Repository boundaries
src/server.py: thin application composition, MCP registration, lifecycle, transport mounting, middleware, and health routing.src/tools/: focused implementations of MCP runtime tools.src/resources/: MCP runtime resources.src/prompts/: MCP runtime prompt templates and helpers.scripts/: PowerShell and POSIX deployment and provisioning guards.azure.yaml:azdhook wiring for deployment only.pyproject.tomlanduv.lock: Python and dependency source of truth.VERSIONandCHANGELOG.md: component release version and history..github/agents/: GitHub Copilot engineering roles..github/skills/: reusable engineering procedures..github/instructions/: path-scoped implementation rules.
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 · 180 lines · 1,862 tokens per session scan A e6978552cb8a
gpt-rag-mcp AGENTS.md is an instructions file published in the GitHub repository Azure/gpt-rag-mcp (22 stars, last pushed 10d ago), licensed MIT. It adds 1,862 tokens to every session, about $0.0074 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 2026-08-30.
gpt-rag-mcp AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| gpt-rag-mcp AGENTS.mdAzure/gpt-rag-mcp | Instructions file | 22 | 10d ago | MIT | A | 1,862 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |