mcp-agent-reliability
MCP server that scores tool descriptions, estimates token costs, simulates agent tool selection, and generates reliability reports to help AI agents choose the right tools and reduce wasted tokens.
README
mcp-agent-reliability
Make your AI agents more reliable.
This MCP server acts like a reliability coach for your agents.
It helps you:
- Score how clear your tool descriptions are (so the agent picks the right one)
- Estimate how many tokens your tools will cost
- Simulate which tool an agent would choose for a task
- Generate simple test prompts
- Get a full reliability report
Built for entrepreneurs and teams who are tired of agents calling the wrong tools and burning money.
Why this exists (simple story)
Imagine you give a 10-year-old child a big list of 30 toys and say “go play with the right one”.
If the labels are confusing, the child will pick the wrong toy.
AI agents are the same.
When you connect many MCP servers, the agent sees a long menu of tools.
If the descriptions are vague, it picks the wrong tool → wasted tokens → failed tasks.
This server is the “label checker” and “practice teacher” for that menu.
Quick start
# clone
git clone https://github.com/princeruhulofficial/mcp-agent-reliability.git
cd mcp-agent-reliability
# install
npm install
# build
npm run build
# run (stdio)
npm start
Add to Claude Desktop / Cursor / any MCP client
{
"mcpServers": {
"agent-reliability": {
"command": "node",
"args": ["/absolute/path/to/mcp-agent-reliability/dist/index.js"]
}
}
}
Or with npx (after publish):
{
"mcpServers": {
"agent-reliability": {
"command": "npx",
"args": ["-y", "mcp-agent-reliability"]
}
}
}
Tools
| Tool | What it does |
|---|---|
score_tool_description |
Gives a 0-100 score + reasons + suggestions for a tool description |
estimate_token_cost |
Rough token count for a list of tools |
simulate_tool_choice |
Predicts which tool an agent would pick for a prompt |
generate_agent_tests |
Creates 3 test prompts you can run against your agent |
reliability_report |
Full summary of scores + token estimates |
All tools are pure computation — no paid API keys required.
Example
Score a description:
Tool: score_tool_description
name: create_invoice
description: Create a new invoice for a customer. Requires customer_id and amount. Returns invoice_id.
You get something like:
{
"score": 85,
"reasons": ["Good length...", "Mentions inputs or outputs..."],
"suggestions": [],
"interpretation": "Excellent — agent should pick this tool reliably"
}
Tech
- TypeScript
- Official
@modelcontextprotocol/sdk - Stateless-friendly (works with 2026 MCP updates)
- Zero external cost for core features
Roadmap
- [ ] Optional LLM-backed scoring (when you want higher accuracy)
- [ ] Hosted version with dashboard
- [ ] Integration with progressive disclosure patterns
License
MIT
Made with ❤️ for the Prevalid community
Founder: Prince Ruhul
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