--- title: Free MCP Server Scorecard: Check Your Tools in 10 Minutes description: Free MCP scorecard: paste your tools/list to see token size, heaviest tools and missing annotations, plus a 15-point checklist with targets from real runs. canonical: https://spiritroom.app/tools/mcp-scorecard/ published: 2026-10-21 updated: 2026-10-21 --- > Markdown version of https://spiritroom.app/tools/mcp-scorecard/ for agents. Index: /llms.txt [Blog](/blog/) / [Test MCP servers with agents](/guides/test-mcp-servers-with-agents/) # MCP server scorecard: check your tools the way agents will meet them Before you run a single agent, you can catch a lot: a tool list that eats 68,000 tokens, write tools marked safe, descriptions that bury the point. Paste your tools/list below and check it in your browser. Then use the checklist for what only agent runs can show. Leonid Bugaev · Published 21 Oct 2026 **TL;DR** - **Paste your tools/list** to get tool count, a rough token size, the five heaviest tools, write-looking tools without annotations, and long first lines. Nothing leaves your browser. - **Our example server:** 99 tools, 68,286 tokens; a 46,253-token default list call; a 12,689-token error; 2 spending tools marked non-destructive. - **15 checks in three layers:** server (no model needed), agent behaviour per app, and outcome and cost. - **Targets are starting budgets** from our runs, not standards: instructions under ~2,000 characters, default results around 5,000 tokens, errors a few hundred. [Paste your tools/list](#checker)[The 15-point checklist](#checklist)[What the checker can't tell you](#what-next)[How we measured](#how-we-measured)[FAQ](#faq) ## Paste your tools/list Paste the JSON from a `tools/list` response: either the whole response or just the `tools` array. Everything runs in this page; nothing is sent. Check my tools Need the JSON? In [MCP Inspector](https://modelcontextprotocol.io/docs/draft/tools/inspector), connect and list tools, or use its CLI to print the `tools/list` result. ## The 15-point checklist From [how to measure MCP server quality](/blog/measure-mcp-server-quality/). Targets are starting budgets from our runs; the last column is a 99-tool production server we tested on 16 Oct 2026. ### Layer 1: server checks (no model needed) | # | Check | Starting target | Example server | | --- | --- | --- | --- | | 1 | Tool-list size (tokens) | Know it; watch the heaviest tools | 68,286 for 99 tools | | 2 | Server instructions length | Under ~2,000 characters, key rule first | 5,092 characters | | 3 | Default result size (each read tool with `{}`) | ~5,000 tokens | 46,253 for the main list | | 4 | Data sent twice (text + structured) | Know which half each app reads | 27 of 34 read tools | | 5 | Error size (fixed bad calls) | A few hundred tokens | 12,689 on one tool; 110–150 on others | | 6 | Error guidance | “Ask the user” only for real decisions | All 3 validation errors said a person must decide | | 7 | Annotation accuracy | Every spend or start marked destructive | 2 spending tools non-destructive; 1 launch tool idempotent | | 8 | Self-noise in feeds | Agent's own calls excluded | 152 of 200 events | **Want the agent half of the scorecard?** Layers 2 and 3 need real runs. We run your users' jobs through Claude Code, Codex and the other apps they use and fill in every row, with ranges. [Book a pilot →](/#contact) ### Layer 2: agent behaviour, per app (needs runs) | # | Check | Starting target | Example server | | --- | --- | --- | --- | | 9 | Up-front cost per request | Know it per app | Codex +0; Claude Code +1,715; OpenCode 1 +73,415 | | 10 | Discovery rate | Every run, every app | Codex 72/80 (81–95%); Claude Code 40/40 | | 11 | Right first call | Every run | Mock: 24/24 with a start-here hint; 1/24 without | | 12 | Refused, cut or spilled results | None on main jobs | Claude Code 23/40 runs; OpenCode 24/40 | | 13 | Repeat calls | Rare, and explained | Codex 13/40; Claude Code 0/40 | ### Layer 3: outcome and cost | # | Check | Starting target | Example server | | --- | --- | --- | --- | | 14 | Task pass rate (pass/N, range) | Ranges that don't overlap your last release | Claude Code 74/80; Codex 69/80; OpenCode 39/40 | | 15 | Tokens per task | Falling release over release | ~222k / 221k / 342k per read question | Token totals in Layer 3 are each app's own usage figures, so compare within an app, not across apps. ## What the checker can't tell you A clean tools/list is necessary, not enough. Our example server listed all its tools correctly and Codex still missed them in 8 of 80 runs. Layers 2 and 3 need real agent runs, repeated, scored as pass/N with a range. See [what MCP Inspector can't catch](/blog/mcp-inspector-vs-agent-testing/), [how to report pass rates](/blog/agent-pass-rates-confidence-intervals/) and the full method in [how to test an MCP server with real AI agents](/guides/test-mcp-servers-with-agents/). **Go deeper:** [Reduce MCP tool response size](/blog/reduce-mcp-tool-response-size/), [How many MCP tools is too many?](/blog/how-many-mcp-tools-is-too-many/), [Tool annotations agents rely on](/blog/mcp-tool-annotations-destructive-hint/). ## How we measured - **Example values:** a 99-tool production MCP server, direct calls and live read-only agent runs (Claude Code 2.1.301, Codex CLI 0.161.0, OpenCode 1.18.34), 16 Oct 2026; tokens with o200k\_base unless they are an app's own usage figures. Right-first-call figures are from a mock with the same tool list, 18 Oct 2026. - **The checker:** estimates tokens as characters ÷ 4 and flags write-like tool names by a word list. Both are rough; check flagged tools by hand. ## FAQ ### How do I check how many tokens my MCP tools use? Get your server's tools/list response (for example from MCP Inspector or its CLI) and paste the JSON into the checker on this page. It estimates tokens as characters ÷ 4, which is rough; for exact numbers count with the tokenizer of the model you care about. Our example server's 99 tools were 68,286 tokens with o200k\_base. ### What should an MCP server score on? Three layers: server checks you can run without a model (list size, instructions, default result size, duplicates, error size and wording, annotations, self-noise), agent behaviour per app (up-front cost, discovery, first call, refused or cut results, repeat calls), and outcome (pass rate and tokens per task). ### Does the checker send my tools anywhere? No. It runs in your browser. The page has standard analytics, but the pasted text is never sent. ### What is a good tools/list size? There is no fixed limit, but it matters most in apps that load every definition up front: OpenCode 1 added 73,415 tokens per request for our example server. Know your number and which tools make it heavy. **Want the agent half of the scorecard?** Layers 2 and 3 need real runs. We run your users' jobs through Claude Code, Codex and the other apps they use and fill in every row, with ranges. [Book a pilot →](/#contact) ## Keep reading - Up[How to test an MCP server with real AI agents (guide)](/guides/test-mcp-servers-with-agents/) - Related[How to measure MCP server quality: the agent scorecard (2026)](/blog/measure-mcp-server-quality/) - Related[MCP tool-list token calculator: what your tools cost in Claude Code, Codex and OpenCode](/tools/mcp-token-cost/)