Skip to content
cccskills
FreePublished on GitHub

mcp-release-qa

Check an MCP server before release through a real client session. Compare available features with source code and documentation, test invalid requests and installation, and produce a verdict backed by reproducible commands and responses.

OriginalShow the original description

Verify an MCP server before release by exercising a real protocol session, comparing runtime capabilities with source and documentation, testing failure paths, and recording reproducible evidence. Use when shipping or reviewing an MCP server, tool, resource, prompt, catalog, or install path.

See how to install

Good for

  • Checking an MCP server before release
  • Comparing live features with source code and documentation
  • Testing invalid requests and error responses
  • Verifying the documented installation process
  • Preparing a release report with reproducible evidence

Files included (1)

  • SKILL.md7.0 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

MCP Release QA

Test the server that users will run. A schema review or a passing unit test is not runtime evidence.

This skill complements security review. It focuses on protocol behavior, published-contract drift, transport correctness, and reproducible release evidence.

Rules

  • Run checks against a fresh server process built from the candidate revision.
  • Keep initialize, notifications/initialized, discovery, and invocation in the same session. A new process is a new STDIO session.
  • Treat source registrations as implementation truth and public documentation as a contract that must match it.
  • Record exact commands and raw responses. Do not replace missing evidence with "looks correct."
  • Do not invoke mutation-capable tools against production data. Use fixtures, a sandbox, or stop and name the missing safe test environment.
  • Derive the expected capability inventory from the candidate source on every run.

1. Establish the release surface

Identify:

  • candidate commit and build command;
  • server entry point and transport: STDIO, Streamable HTTP, or SSE;
  • supported MCP protocol versions;
  • source files that register tools, resources, resource templates, and prompts;
  • generated catalogs, manifests, README tables, and install instructions;
  • existing protocol, integration, and smoke-test commands.

Prefer repository-native commands. Inspect package.json, pyproject.toml, Makefile, CI workflows, and contributor instructions before inventing a test harness.

2. Start a clean server

Build the candidate and start the documented entry point with test-safe configuration. Capture:

  • the exact command;
  • commit SHA;
  • environment variable names, with values redacted;
  • stdout, stderr, and exit status;
  • the endpoint or child-process transport used by the client.

For STDIO, stdout is protocol-only. Logs, banners, and stack traces belong on stderr. For HTTP transports, record the status, relevant MCP headers, and session identifier handling without printing credentials.

If the server cannot start from its documented instructions, report that as a release failure and preserve the startup error verbatim.

3. Exercise one complete session

Run this sequence through a real MCP client or the repository's integration harness:

  1. initialize with a protocol version the server claims to support.
  2. Confirm the negotiated version and advertised capabilities.
  3. Send notifications/initialized.
  4. Call ping.
  5. Call each supported discovery method:
    • tools/list
    • resources/list
    • resources/templates/list
    • prompts/list
  6. Exercise at least one representative read-only item from every advertised capability class.
  7. Follow pagination until no cursor remains when a list method is paginated.

Do not send post-initialization requests through separate one-shot processes. That accidentally tests several incomplete sessions instead of one valid session.

4. Prove inventory parity

Build four inventories from current evidence:

SurfaceEvidence
SourceRegistered tool, resource, template, and prompt definitions
RuntimeResults from the live discovery methods
Generated metadataCatalogs, manifests, or generated indexes
DocumentationREADME, reference pages, and install output

Compare by stable identifier. Report:

  • source entries missing at runtime;
  • runtime entries absent from metadata or documentation;
  • stale names, descriptions, arguments, URIs, or prompt parameters;
  • documented install commands that do not start the candidate server.

Regenerate derived files with the repository's own build command, then fail if the working tree still contains unexplained generated changes.

5. Check published contracts

For every discovered item, verify the runtime definition against its source:

Tools

  • Name and description are stable and specific.
  • inputSchema defines types, required fields, enums, and bounds where needed.
  • Unknown properties are rejected when the tool contract is closed.
  • Mutation, idempotence, read-only, and open-world annotations match behavior.
  • Successful calls conform to outputSchema when one is published.
  • Errors are protocol errors or structured tool failures, not leaked stack traces.

Resources and templates

  • URIs and MIME types match the registered definitions.
  • Static resources are readable.
  • Template parameters are validated before resolution.
  • Missing or forbidden resources fail explicitly.

Prompts

  • Required and optional arguments match discovery output.
  • prompts/get returns usable messages for valid arguments.
  • Missing required arguments and unknown prompt names fail explicitly.

6. Test failure paths

At minimum, probe:

  • a request before initialization completes;
  • malformed JSON or an invalid JSON-RPC envelope;
  • an unknown method;
  • an unsupported protocol version;
  • repeated initialization;
  • unknown tool, resource, and prompt names;
  • missing, extra, wrong-type, and out-of-bounds arguments;
  • a request at the documented transport-size limit and one beyond it;
  • a controlled internal failure with credentials and stack traces redacted.

Verify that each response has the correct request ID, a useful error message, and no successful side effect. For STDIO, also confirm every stdout line is a complete protocol message and a healthy session leaves stderr clean unless the server explicitly documents diagnostic output.

7. Smoke-test installation

When the project publishes an install command:

  1. Create a temporary destination outside the source checkout.
  2. Run the public install command exactly as documented.
  3. Start the installed artifact without relying on files from the source tree.
  4. Repeat initialization, discovery, and one read-only invocation.
  5. Remove the temporary destination after preserving the command output.

An install string that was only inspected is unverified.

8. Report the evidence

Use this format:

# MCP Release QA

Candidate: [commit]
Transport: [STDIO | Streamable HTTP | SSE]
Verdict: PASS | PASS WITH CAVEATS | FAIL

## Commands and results
- `[exact command]` — [exit status and result]

## Session transcript
- initialize: [result]
- discovery: [result]
- representative calls: [result]
- negative paths: [result]

## Parity
| Identifier | Source | Runtime | Metadata | Docs | Result |
|---|---|---|---|---|---|

## Findings
| Severity | Evidence | Impact | Narrowest fix |
|---|---|---|---|

## Missing evidence
- [check that could not run and why]

Use FAIL for a server that cannot start, complete a valid session, keep the transport parseable, or safely reject invalid input. Use PASS WITH CAVEATS only for bounded documentation or metadata drift that does not misrepresent a dangerous capability. Otherwise use PASS.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.

  • Get oriented in an unfamiliar codebase
  • Prepare documentation for a project handover
  • Compare documented architecture with implementation
github/awesome-copilot40.2KUpdated Oct 17, 2026

Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.

  • Assessing a repository’s readiness for AI agents
  • Prioritizing improvements from assessment results
  • Reviewing scores under an organization’s own policy
github/awesome-copilot40.2KUpdated Oct 17, 2026

Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.

  • Create project instructions for VS Code Copilot
  • Refresh agent rules after project changes
  • Split monorepo instructions by project area
github/awesome-copilot40.2KUpdated Oct 17, 2026

Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.

  • Set shared readiness standards across an organization
  • Focus assessments on AI tooling
  • Adjust the importance of individual checks
github/awesome-copilot40.2KUpdated Oct 17, 2026

Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.

  • Identify ads and keywords to pause
  • Find campaigns and audiences worth scaling
  • Assess whether A/B test results are meaningful
github/awesome-copilot40.2KUpdated Oct 17, 2026

Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.

  • Add beginner-friendly explanations to existing code
  • Document the reasoning behind syntax and design choices
  • Adjust comment depth for readers with different experience
github/awesome-copilot40.2KUpdated Oct 17, 2026

See all skills by github

Report a problem with this skill