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MCP Endpoint Lint - handshake, tool schemas, JSON-RPC errors

All four checks, one machine-readable verdict

score_card
Read-onlyIdempotent

FIRST CALL, needs nothing: {"name":"whoami","arguments":{}} — Run handshake_report, tools_list_report, error_conformance and discovery_report against one endpoint and return a single verdict: a score out of 100 (handshake 30, tool schemas 30, error conformance 25, discovery 15), a letter grade, every finding by severity with the section it came from, and the full detail of each section underneath. This is the tool to call from a monitor: the score is stable enough to alert on and the findings say what to fix. Makes up to 19 requests to the URL you give it, 6 s each, and is rate-limited per caller and per target host. Example: url='https://mcp.example.com/mcp' — or {} to score the built-in fixture (it gets a D) with no outbound request at all.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe MCP endpoint to lint — the URL you POST JSON-RPC to, e.g. https://mcp.example.com/mcp. Not stored anywhere. This server refuses its own publisher, IP literals and private names.

TDQS

A4.1/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/non-destructive behavior, and the description adds substantial operational detail: up to 19 requests, 6-second timeouts, per-caller and per-host rate limiting, URL restrictions, and the no-outbound fixture option. This goes well beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense with useful operational facts: weights, output contents, request volume, rate limits, and examples. However, it opens with a confusing 'FIRST CALL... whoami' phrase that seems off-topic for this tool and blurs the description's focus.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex aggregator with no output schema, the description covers the return structure, individual check weights, use case, rate limits, and URL behavior. The main gaps are the unresolved {} fixture inconsistency and lack of error-behavior detail when requests fail, but overall it is largely complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema's url description is strong, but the description introduces a contradictory alternative: 'or {} to score the built-in fixture' conflicts with required url and additionalProperties=false. This misleading extra guidance degrades an otherwise clear parameter definition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the exact operation: run handshake_report, tools_list_report, error_conformance, and discovery_report against one endpoint and return a single verdict. It clearly differentiates this aggregate tool from its siblings by stating the combined checks, weighted score, letter grade, and findings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says this is the tool to call from a monitor because the score is stable enough to alert on and findings indicate what to fix. It does not explicitly say when to use the individual report tools instead, but the aggregation framing makes the distinction clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0
Disambiguation5/5

Each tool has a clearly distinct role: the four check tools target separate protocol aspects, score_card is explicitly the aggregate runner, example is a fixture demo, and whoami is self-inspection. Even where score_card composes the other checks, descriptions make the relationship unambiguous.

Naming Consistency3/5

Names are all lowercase and underscore-separated, but the pattern is mixed: discovery_report, handshake_report, and tools_list_report share a report suffix, while error_conformance, score_card, example, and whoami do not follow it. The names are readable and descriptive, but not fully predictable.

Tool Count5/5

Seven tools is well-scoped for an endpoint linter: four specialized checks, one aggregate score, one demo helper, and one identity/rate-limit introspection tool. Each tool earns its place and the count supports both granular investigation and high-level monitoring.

Completeness5/5

The tool surface covers the stated domain end to end: pre-handshake discovery, initialize/handshake behavior, tools/list schema validation, and JSON-RPC error conformance, plus an aggregate score_card. No obvious dead ends or missing operations exist within the server's declared purpose.

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