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QA Engineering MCP Hub

QA Engineering MCP Hub

by yafifaisal

QA Engineering MCP Hub

QA Engineering MCP Hub is a local-first, cross-platform FastMCP foundation for governed QA workflows. Milestones 00 and 01 provide the MCP foundation and secure local configuration control plane. All external providers and QA execution features remain explicitly NOT_IMPLEMENTED or SCAFFOLDED.

What works through Milestone 01

  • qa-mcp serve starts a standalone FastMCP 4 server over stdio.

  • hub_health reports local process readiness.

  • hub_capabilities separates callable features from future work.

  • qa-hub://status is a read-only JSON MCP resource.

  • qa_hub_orientation is a reusable MCP prompt.

  • qa-mcp doctor, qa-mcp capabilities, qa-mcp --help, and qa-mcp --version provide local CLI diagnostics.

  • Pydantic Settings validates non-secret QA_MCP_ environment configuration.

  • Portable configuration paths and simulated Windows/macOS/Linux behavior are tested.

  • Versioned YAML supports named profiles, multiple connections per provider, repository/workspace references, execution preferences, and strict validation.

  • Credentials are referenced through an OS keyring or explicitly named environment variables; resolved values are redacted and never serialized.

  • setup, profiles, integrations, config, and clients commands manage and inspect local readiness. Integration tests do not make provider network calls.

  • Codex TOML and native VS Code JSON can be generated without provider credentials.

No provider adapter, provider OAuth exchange, repository or ticket read, test execution, database query, Kafka operation, CI/CD action, test-management action, evidence publication, or release approval is implemented.

Related MCP server: checkyourself

Prerequisites and setup

Install Python 3.12 or newer and uv, then run:

uv sync --frozen
uv run qa-mcp --help
uv run qa-mcp doctor
uv run qa-mcp capabilities
uv run qa-mcp setup
uv run qa-mcp config validate

Start the server:

uv run qa-mcp serve

A stdio MCP server waits for a client and normally appears silent. stdout is reserved for MCP protocol messages.

Codex registration

Use absolute paths for both uv and this repository:

codex mcp add qa_hub -- /ABSOLUTE/PATH/TO/uv run --project /ABSOLUTE/PATH/TO/qa-engineering-mcp-hub qa-mcp serve
codex mcp list

Codex uses .codex/config.toml; native VS Code/Copilot MCP JSON is a separate configuration dialect. See the Codex setup guide and platform guides.

Architecture

The project deliberately separates:

  1. the reusable framework in src/qa_mcp_hub/;

  2. company-specific assets created from templates/qa-workspace/;

  3. per-machine user configuration and credential references.

Read the canonical architecture, decisions, and scaffold manifest before structural changes. Provider status and documentation are indexed in docs/providers/README.md.

Validation

uv lock --check
uv run ruff check .
uv run ruff format --check .
uv run mypy src
uv run pytest -v
uv run python scripts/structure_audit.py
uv build

The progress report records actual executed evidence. Simulated path tests do not constitute live Windows or Linux verification.

Contributing and security

See CONTRIBUTING.md, SECURITY.md, and AGENTS.md. Never commit credentials, customer data, local workspace content, or fabricated integration results.

License

QA Engineering MCP Hub is available under the MIT License.

Available Tools

2 tools
hub_capabilitiesHub CapabilitiesB

Return implemented and planned capabilities without overstating support.

NameRequiredDescriptionDefault

No parameters

Output Schema

NameRequiredDescription
plannedYes
implementedYes

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, but it does add one meaningful behavioral caveat: it returns both implemented and planned capabilities and should not overstate support. It does not state that the operation is read-only, side-effect free, or how 'planned' should be interpreted.

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

Conciseness4/5

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

One front-loaded sentence with no wasted words. The wording is efficient, though the phrase 'without overstating support' is slightly vague and could be sharper.

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?

Because an output schema exists, the description needn't explain return values, and with zero parameters the input side is trivial. It is nearly complete, though a read-only safety note and explicit sibling contrast would close the remaining gap.

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

Parameters4/5

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

The tool takes zero parameters, which is the baseline-4 case. The schema is trivially complete and the description adds no contradictory parameter expectations.

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

Purpose4/5

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

The description gives a specific verb ('Return') and resource ('implemented and planned capabilities'), so an agent can tell this is a capability-discovery tool rather than a health probe. It does not explicitly name or contrast with the sibling hub_health, leaving differentiation partly to inference.

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

Usage Guidelines2/5

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

There is no explicit when-to-use guidance, no mention of the hub_health alternative, and no stated preconditions. The usage is only implied by the word 'capabilities'.

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

hub_healthHub HealthA

Return local server readiness; do not probe future providers.

NameRequiredDescriptionDefault

No parameters

Output Schema

NameRequiredDescription
statusYes
serviceYes
versionYes
transportYes

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; 'Return' implies a read-only check and the future-provider caveat hints at a side-effect-free scope, but auth requirements, cost, and behavior are unstated. The presence of an output schema relieves it of explaining return values, which keeps this at an adequate 3.

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

Conciseness4/5

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

A single compact sentence with the action front-loaded and the constraint immediately after. Nothing is wasted, though the 'future providers' phrasing is cryptic enough to require interpretation.

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 zero-parameter read with an output schema, the definition covers what the tool does and one important scope limit. Only the meaning of 'future providers' and the relationship to hub_capabilities are left open.

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

Parameters4/5

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

The tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies.

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

Purpose4/5

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

States a specific verb ('Return') and resource ('local server readiness'), so the agent knows this is a health/status check rather than a capability listing. The scope caveat ('local') helps separate it from hub_capabilities, though the sibling is never named and 'readiness' is slightly abstract.

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

Usage Guidelines3/5

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

Provides one explicit exclusion ('do not probe future providers'), which is real when-not guidance. However, it never says when to prefer this over hub_capabilities or what 'future providers' means, so the routing guidance is only implied.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updatesv0.1.0
    • First observedhub_capabilities
    • First observedhub_health

TDQS

B3.4/5.0

Scored across 2 tools

Disambiguation4/5

hub_health (readiness/liveness) and hub_capabilities (feature inventory) are conceptually separable and the descriptions reinforce the split. They are still both metadata-only introspection calls, so an agent may occasionally grab one when it wanted the other.

Naming Consistency5/5

Both tools use a clean, identical `hub_<noun>` snake_case pattern. There is no mixing of verbs, casing, or prefixes.

Tool Count2/5

Two tools is very thin for something billed as a 'QA Engineering MCP Hub' — it is a stub surface rather than a scoped toolset. Both tools earn their place, but the count is far below what the stated purpose implies.

Completeness2/5

The surface covers only self-introspection; there are no QA-engineering operations at all (no test discovery, run, results, coverage, or reporting). An agent reaching for this hub for its advertised domain hits an immediate dead end.

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