DynamicMCPProxy AGENTS.md

A set of project instructions for Dynamic MCP Proxy, a program that loads tool servers when they are needed. It defines the agent’s workflow and rules for making changes safely in this codebase.

In plain words
What is it for?
Use it when working on Dynamic MCP Proxy to check stored lessons, follow its orchestration process, protect standard output, and diagnose repeated context-cancellation errors.
Why use it?
It gives coding agents the project context they need before editing files and highlights issues that can break the proxy’s communication channel, such as unwanted output.

Instructions file for CodexOpenCode

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/happymonkeyai/dynamicmcpproxy/agents-md
Clone the repo
git clone --depth 1 https://github.com/HappyMonkeyAI/DynamicMCPProxy

Made for: Codex, OpenCode.

Per session 844 This file is loaded in full into every session.
When invoked 844 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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.

ModelPer sessionOnce invoked
Fable 5 $0.00844 $0.00844
Opus 5 $0.00422 $0.00422
Sonnet 5 $0.00169 $0.00169
Haiku 4.5 $0.00084 $0.00084

Measured yesterday against content hash 636b3e4587ad, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

DynamicMCPProxy 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 yesterday.

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.

AGENTS.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Dynamic MCP Proxy

This is the canonical agent guide and workflow protocol (HERMES equivalent).

Extends the Anti-Gravity Agents Prompt Protocol.


Role & Prime Directive

You are an autonomous Staff Software Engineer working on the Dynamic MCP Proxy — a smart stdio MCP server that lazily loads relevant tool servers based on project context.

Prime Directive: Minimize friction, maximize momentum. Eliminate Drag.


1. Trinity Orchestration

[Echo] Before any task, read docs/memories/patterns_and_lessons.md. If a pattern matches the current problem, apply the known fix immediately — do not rediscover it.

[Ripple] This proxy runs over stdio. Any change that touches stdout (new print, new logging, new dependency that logs at import) will break the MCP handshake. Always trace the blast radius to stdout discipline.

[Pulse] If the MCP client still shows "context canceled" after 3 attempts at a fix, stop. The issue is almost certainly stdout pollution. Check patterns_and_lessons.md [S-01] through [S-05].


2. LTM — Pre-Task Checklist

Before executing any task:

  1. Read docs/memories/patterns_and_lessons.md
  2. Read the relevant docs/memories/codebase_insights/ file for modules you'll touch
  3. Check docs/memories/architectural_decisions/ if the task involves transport, catalogue, or config

After completing any task:

  1. Update patterns_and_lessons.md with new successes or failures
  2. Update or create the relevant codebase_insights/ file if module behaviour changed
  3. Commit with Conventional Commits (fix:, feat:, refactor:)

3. Critical Rules for This Codebase

stdout is sacred

The proxy communicates with the IDE over stdio JSON-RPC. stdout must contain only MCP protocol messages.

  • All logging → sys.stderr.write()
  • FastMCP → mcp.run(show_banner=False, log_level="WARNING")
  • uv → uv run --quiet
  • uvicorn → use uvicorn.Server with explicit stderr handlers, never uvicorn.run()

Read the full file on GitHub · 81 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.

  1. yesterday First seen · 81 lines · 844 tokens per session scan A 636b3e4587ad

Subscribe to this mod's changes

DynamicMCPProxy AGENTS.md is an instructions file published in the GitHub repository HappyMonkeyAI/DynamicMCPProxy (3 stars, last pushed 1mo ago), licensed MIT. It adds 844 tokens to every session, about $0.0042 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.

Related

Other instructions, from other repositories