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.
npx agentmods add instructions/codeprimate/math-mcp/agents-mdgit clone --depth 1 https://github.com/codeprimate/math-mcpWhat 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 | $0.01069 | $0.01069 |
| Opus 5 | $0.00535 | $0.00535 |
| Sonnet 5 | $0.00214 | $0.00214 |
| Haiku 4.5 | $0.00107 | $0.00107 |
Grade A, and why
math-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.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md - Development Guide
Python MCP server providing 27+ tools for symbolic mathematics, statistical analysis, and visualization.
Quick Start
This project uses uv for environment and dependency management.
# Setup (first time)
uv venv
source .venv/bin/activate
uv sync
# Daily workflow
source .venv/bin/activate
ruff check --fix src/ tests/
PYTHONPATH=src pytest tests/ -v
Or use uv run so you don't need to activate the venv:
uv run ruff check --fix src/ tests/
PYTHONPATH=src uv run pytest tests/ -v
Critical Requirements
- Use uv: Create venv with
uv venv, install deps withuv sync. Optionally useuv runfor commands instead of activating the venv. - Always run linter:
ruff check --fix src/ tests/after code changes - Tests require PYTHONPATH:
PYTHONPATH=src pytest tests/ -v
Project Structure
src/math_mcp/ # Source code
tests/ # Test suite
pyproject.toml # Project config
Key Files & Documentation
- README.md - Main project documentation, tool descriptions, usage examples
- docs/skills/math-mcp/SKILL.md - Cursor skill for using Math MCP (4-tool interface, discovery, data prep, visualization); use for math/statistics/charting tasks
- pyproject.toml - Project configuration, dependencies, coverage settings
- env.example - Environment variable reference for HTTP mode
- docs/mcp.json - Example Cursor/Claude Desktop config (stdio Docker)
- docs/mcp.json.http - Example HTTP endpoint config
- docs/claude_desktop_config.json - Claude Desktop example
- docker-compose.yml - Docker Compose configuration
Development Workflow
- Research - Understand requirements and plan
- Implement - Code in
src/math_mcp/, tests intests/ - Lint -
ruff check --fix src/ tests/ - Test -
PYTHONPATH=src pytest tests/ -v - Iterate - Repeat until complete
- Docker -
docker-compose build && docker-compose restart
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 · 131 lines · 1,069 tokens per session scan A 7054728d7915
math-mcp AGENTS.md is an instructions file published in the GitHub repository codeprimate/math-mcp (4 stars, last pushed 5mo ago), licensed MIT. It adds 1,069 tokens to every session, about $0.0053 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.
Other instructions, from other repositories
VCVio AGENTS.md
Instructions for Verified-zkEVM/VCVio, covering vcvio — ai agent guide, fast start, attribution, headers, and docstrings, module scopes and what this project is.
oci-agent CLAUDE.md
Instructions for Netflix-Skunkworks/oci-agent, covering observational causal inference (oci) agent and rules.
relarena CLAUDE.md
Instructions for PriorLabs/relarena: All package notes live in AGENTS.md — read that first.
bio-gene-to-reference-tree copilot-instructions.md
Instructions for Hongda-Zhao/bio-gene-to-reference-tree, a project described as: Auditable agent skill for resolving protein queries, selecting references, and planning reproducible phylogenetic trees.
scholar-agent copilot-instructions.md
Instructions for zfy465914233/scholar-agent, covering global instructions, project context, core constraints, output principles and evidence handling.
gpu-ai-skills CLAUDE.md
Instructions for intel/gpu-ai-skills, covering claude.md, what this repository is, repository structure, commands and validation (required before any skill change).