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.
git clone --depth 1 https://github.com/Chess-analysis-mcp/tintins-chess-analysisWrote 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/mcp/chess-analysis-mcp/tintins-chess-analysis/chess)<a href="https://agentmods.dev/mcp/chess-analysis-mcp/tintins-chess-analysis/chess"><img src="https://agentmods.dev/badge/mcp/chess-analysis-mcp/tintins-chess-analysis/chess/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/mcp/chess-analysis-mcp/tintins-chess-analysis/chess"><img src="https://agentmods.dev/badge/mcp/chess-analysis-mcp/tintins-chess-analysis/chess.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
chess 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 9d 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.
What it actually says
{
"chess": {
"command": "uv",
"args": [
"run",
"--directory",
".",
"python",
"-m",
"server.mcp_server"
],
"env": {
"CHESS_USERNAME": "",
"STOCKFISH_PATH": "",
"CHESS_ALIASES": "",
"LICHESS_TOKEN": "",
"CHESS_PROFILE_RECENT": "100",
"CHESS_PROFILE_LIFETIME": "all"
}
}
}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.
- 9d ago First seen · 21 lines scan A f68d80cc386a
chess is an MCP server published in the GitHub repository Chess-analysis-mcp/tintins-chess-analysis (41 stars, last pushed 1mo ago), licensed MIT. Its token cost is not measured: an MCP server costs its tool schemas, not its config file. 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.
Other mcp servers, from other repositories
chess-uci-mcp
MCP server to connect to the chess engines using UCI protocol. Runs locally from the chess-uci-mcp Python package.
chess-mcp-server
A Model Context Protocol (MCP) server for playing Chess with AI Agents. Runs locally from the chess-mcp-server Python package.
mnemos-core
MCP server "mnemos-core" as configured in ncz-os/mnemos. Runs locally from the mnemos-core Python package.
figma
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot. Runs locally from the figma-developer-mcp npm package. Needs 1 environment variable to run.
2009scape-wiki
MCP server "2009scape-wiki" as configured in arsalan-anwari/2009scape-wiki-api. Runs locally from the . Python package. Needs 1 environment variable to run.
knowledge-inbox
MCP server "knowledge-inbox" as configured in lyc403223157-source/knowledge-inbox. Runs locally from the knowledge-inbox Python package.