mcp-optimizer CLAUDE.md

Project-specific instructions for developing ToolHive MCP Optimizer, a server that helps AI clients find and use tools from multiple MCP servers through one connection. MCP servers provide tools that AI applications can call.

In plain words
What is it for?
Use it when adding code, running checks, or implementing the command-line interface for the MCP Optimizer project.
Why use it?
It gives the project a consistent development workflow and addresses the difficulty of managing many separate AI tools.

Instructions file

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/stackloklabs/mcp-optimizer/claude-md
Clone the repo
git clone --depth 1 https://github.com/StacklokLabs/mcp-optimizer
Per session 817 This file is loaded in full into every session.
When invoked 817 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 $0.00817 $0.00817
Opus 5 $0.00409 $0.00409
Sonnet 5 $0.00163 $0.00163
Haiku 4.5 $0.00082 $0.00082

Measured 2d ago against content hash 1eb3fbedf902, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mcp-optimizer CLAUDE.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.

CLAUDE.md · 52 lines

How it starts

The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Project

The general purpose of the ToolHive MCP Optimizer is to develop a MCP server that acts as an intelligent intermediary between AI clients and multiple MCP servers. The MCP Optimizer server addresses the challenge of managing large numbers of MCP tools by providing semantic tool discovery, caching, and unified access through a single endpoint.

Technical considerations

  • Use uv as package manager. uv add <package> for adding a package. uv add <package> --dev for development packages for linting and testing
  • Use the taskfile for running linting and formatting
    • task format for running formatters
    • task lint for running linters
    • task typecheck for running typecheckers
    • task test for running tests
  • Use pydantic for validating structured data
  • pyproject.toml should be the central place for configuring the project, i.e. linters, typecheckers, testing, etc
  • Always prefer to use native Python types over custom types, e.g. use list instead of List, dict instead of Dict, etc.
  • Prefer using uv run python -c "import this" instead of python -c "import this". This ensures that the correct python version and environment is used.

Code Structure

  • The main server code is located in src/mcp_optimizer/server.py
  • The database configuration and CRUD operations are in src/mcp_optimizer/db/
  • The mcp-optimizer CLI implementation is located in src/mcp_optimizer/cli.py

Development Workflow

  • After adding or modifying code, use task format to automatically format the code
  • Then run task lint and task typecheck to identify and fix any remaining errors
  • Some formatting and linting errors can be automatically resolved by running task format
  • Use task test to run the test suite and ensure all tests pass

CLI Implementation

  • Follow the pattern that every new command should group big functionality and add as parameters the inputs for that big functionality
  • Prefer using logger for printing in the CLI instead of using click.echo

Read the full file on GitHub · 52 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. 2d ago First seen · 52 lines · 817 tokens per session scan A 1eb3fbedf902

Subscribe to this mod's changes

mcp-optimizer CLAUDE.md is an instructions file published in the GitHub repository StacklokLabs/mcp-optimizer (11 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 817 tokens to every session, about $0.0041 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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