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1 ★ · TimurRakhmatullin86/mcp-drill · read from the GitHub search API · (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list · type: MCP server
Harvest history
first seen 2026-10-09 · last seen 2026-10-16 · seen 32× · listed by 7 sources
Score
score 703 · 1 ★ · 7 sources · mcp
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repository TimurRakhmatullin86/mcp-drill;first catalogued 2026-10-09;last seen 2026-10-16。There is no official certification or quality rating here — we record sources and dates only.
**Fault injection and reliability testing for MCP servers and AI agents.** Wrap any Model Context Protocol server in one command; inject timeouts, malformed JSON-RPC, truncated and corrupted-but-valid tool outputs; measure whether the server degrades cleanly — and whether your agent *notices* or silently acts on the garbage. MCP is JSON-RPC over stdio/SSE with bidirectional notifications, so ordinary HTTP fault-injectors and chaos tools don't fit. mcp-drill speaks MCP: it sits transparently between an MCP client and a backend server and perturbs the traffic, so you can test failure paths in CI without a live LLM. > **Finding:** across 31 popular MCP servers (including Microsoft Learn, Hugging Face, Cloudflare and > DeepWiki), only **3% of tools declare an output contract that would reject a corrupted response**. > See the live scorecard. Why Real MCP deployments fail in ways integration tests never cover: a tool times out, a server returns a well-formed-but-wrong payload, a response is truncated mid-stream. Most agents were never exercised against these paths. mcp-drill makes them reproducible: - 🧪 **Fault injection** — deterministically inject timeouts, malformed/oversized/truncated responses, corrupted-but-schema-valid payloads, dropped tools, and latency. - 🎬 **CI-first** — a CLI and a GitHub Action; no live model or API keys required in the loop. - 📊 **Reliability scorecard** — a model-free scan that grades how a server responds to bad input and how machine-checkable its tool output contracts are. Install Quickstart What it measures (model-free) The scan command is deterministic and involves no language model, so its numbers are properties of the server and the protocol — not of whichever agent happens to call it: 1. **Error conformance** — on invalid requests (unknown method, unknown tool, missing required arguments), does the server return a spec-compliant JSON-RPC error, a proper tool error, or does it hang / crash / answer as if nothing was wrong? 2. **Output-contract coverage** — what fraction of a server's tools declare a machine-checkable outputSchema at all? Tools without one give downstream validators nothing to check. 3. **Output-contract enforceability** — of the tools that declare an outputSchema, how many would