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tcm-mcp

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tcm-mcp — TCM MCP Server (Epic 1: Test Case CRUD)

A stdio MCP server that gives AI agents (Torque, triage-e2e, Claude agents) a stable tool interface to read and write TCM test cases — without touching the database schema directly.

It is a thin client: every tool call proxies a TCM REST endpoint. ID resolution, validation, display_id generation, the in_cicd lock, and soft-delete scoping all happen inside TCM. Agents reference cases by display_id (e.g. APA-3); internal UUIDs are never exposed.

Full design: docs/features/mcp-e1-test-case-crud.md (in the main TCM repo).

Tools

Tool

Purpose

list_projects

Discover the projects you can see (project_id + name). Search by name; default 50, max 200.

search_suite

Resolve a suite name/prefix → suite_id within a project (project_id or project_name).

list_suites

List every suite in a project — each with suite_id, name, prefix, group (role label), test_case_count.

list_test_cases

Lightweight filterable list (display_id, title, automation_status, priority). Default 50, max 200.

get_test_case

Full detail + steps, by display_id.

create_test_case

Create a case with steps — dry-run → approval → commit (see below).

update_test_case

Partial update; steps are full-replace when provided — same dry-run flow.

Reads exclude trashed (soft-deleted) cases. Writes require the dry-run flow.

Project scoping. search_suite, list_suites, and list_test_cases scope by project. Pass a project_id (UUID) directly, or a project_name — the server resolves the name to an id via list_projects (case-insensitive exact match; an unknown name returns NOT_FOUND and an ambiguous one returns AMBIGUOUS with the candidate ids). Use list_projects first to discover ids. list_test_cases with no project returns cases across every project you can see.

Related MCP server: TestRail MCP Server

Requirements

  • Node.js ≥ 18 (for npx and the global fetch).

  • Git read access to JoinFullStackDev/tcm-mcp — the package is distributed by git URL, not published to npm. On headless hosts (OpenClaw/Torque) a git token must be present in the environment.

  • That's it for the TCM URL: it defaults to production (https://tcm-ochre.vercel.app), so there's nothing to look up or set. You just need to authenticate (Quickstart).

Because it's distributed by git URL, npx clones the repo and builds from source on first run (via the package's prepare → tsc step), so the first launch is slower. Subsequent runs are cached.

Quickstart

Zero-config: the production TCM instance (https://tcm-ochre.vercel.app) is baked in as the default, so you never set TCM_BASE_URL. Point at a different instance only if you self-host (see Environment variables).

Prerequisite — git access. This package is fetched by git URL from a private repo, so the machine running it needs git read access (gh auth login, or a git token for headless hosts). Node ≥ 18 must be installed. On macOS, GUI-launched Claude Desktop may not see your shell PATH — if the server fails to start, use an absolute path to npx in the config (find it with which npx).

1. Register the server

Claude Code — one command, nothing to edit by hand:

claude mcp add tcm --scope user -- npx --yes github:JoinFullStackDev/tcm-mcp#v1.4.0 --stdio

--scope user makes it available in every project. (Drop it to scope to the current project; Claude Code writes the .mcp.json for you.)

Claude Desktop — no CLI, so add it to the config file once:

  1. Settings → Developer → Edit Config — this creates and opens claude_desktop_config.json for you (no folder to make yourself):

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

    • Windows: %APPDATA%\Claude\claude_desktop_config.json

  2. Add the tcm entry (merge into mcpServers if it already exists), then fully quit + reopen Claude Desktop:

{
  "mcpServers": {
    "tcm": {
      "command": "npx",
      "args": ["--yes", "github:JoinFullStackDev/tcm-mcp#v1.4.0", "--stdio"]
    }
  }
}

Pin to a tag (#v1.4.0), not a branch — a branch ref re-resolves on every launch and can trip the 30 s MCP startup timeout. No env block is needed.

2. Sign in

The server starts even before you've logged in — it just exposes a login tool. So the easiest way (works in Claude Desktop and Claude Code, no terminal):

Just ask Claude: "Log me into TCM."

Claude calls the login tool, a browser opens once for Google sign-in, and the server stores a session it then keeps refreshed. The other tools light up immediately after. (Playwright is auto-installed on first login — a one-time ~100 MB browser download into ~/.tcm-mcp.)

Prefer a terminal? Same thing, run once:

npx --yes github:JoinFullStackDev/tcm-mcp#v1.4.0 login

Details: Auto-refreshing login.

If you'd rather edit .mcp.json directly (Claude Code project or ~/.claude/.mcp.json), the minimal entry is just command + args as shown above. To use the legacy static-token mode instead of a login session (e.g. CI that already has a JWT), add an env block — note it expires ~1h and refreshing it needs a full client restart:

{
  "mcpServers": {
    "tcm": {
      "command": "npx",
      "args": ["--yes", "github:JoinFullStackDev/tcm-mcp#v1.4.0", "--stdio"],
      "env": { "TCM_USER_TOKEN": "${TCM_USER_TOKEN}" },
    },
  },
}

Auth modes

The server resolves its mode at startup. Precedence: CLUTCH_API_KEY → login session file → TCM_USER_TOKEN.

Mode

Selected by

Sends

Use for

Attribution

Refreshing token (interactive)

a session file (npm run login)

Authorization: Bearer <jwt>

Claude Code, human in the loop

The real user (their Supabase session)

Static token (legacy)

TCM_USER_TOKEN

Authorization: Bearer <jwt>

CI / scripts injecting a JWT

The real user (their Supabase JWT)

Clutch key (headless)

CLUTCH_API_KEY

X-Clutch-Key

Torque via Clutch/OpenClaw

The service profile — see MCP_AGENT_USER_ID

In refreshing mode the server auto-renews the access token before expiry and again on any 401 (retrying the request once), and persists the rotated refresh token back to the session file. In static and clutch modes a 401 is terminal (nothing to refresh).

In headless mode you must also set MCP_AGENT_USER_ID, or create/update will fail on the created_by/updated_by NOT NULL constraint. The server prints a startup warning if it's missing. When set, the server forwards it to TCM as an X-Agent-User-Id header (trusted only alongside a valid X-Clutch-Key), so each agent attributes its own writes; TCM falls back to its own MCP_AGENT_USER_ID env if the header is absent. (Requires TCM with the matching write-attribution support.)

Auto-refreshing login (recommended)

The login helper signs you into TCM in a browser once and writes a session file the server then uses to keep itself authenticated indefinitely — no ~1h token churn, no client restarts.

# no clone needed — runs straight from the git URL:
npx --yes github:JoinFullStackDev/tcm-mcp#v1.4.0 login

# ...or, from a local clone of this repo:
npm run login

  • Opens a browser only if there's no valid saved session; later runs refresh silently (headless, no window).

  • Playwright is installed for you on first login. It is deliberately not a server dependency (keeps npx <server> installs lean ~50 MB), so the login helper installs playwright + Chromium once into ~/.tcm-mcp (a ~100 MB one-time download) if they aren't already present. You do not need a separate "Playwright MCP" — the login is fully self-contained.

It writes ~/.tcm-mcp/session.json (mode 0600) containing the Supabase project URL, anon key (public), and the access + refresh tokens. From then on the MCP server (mode “refreshing token”) mints fresh access tokens on demand.

  • Session file location: ~/.tcm-mcp/session.json, override with TCM_SESSION_FILE.

  • Browser profile: ~/.tcm-mcp/browser, override with TCM_BROWSER_PROFILE.

  • Security: the refresh token is a long-lived credential — the file is 0600 and must never be committed or shared. Supabase rotates the refresh token on every refresh; the server persists the new one atomically.

  • When it expires: if the refresh token is ever revoked/expired, tool calls fail with a clear “run npm run login” message. Re-run the helper.

  • Anon key capture: the helper sniffs the public apikey header from Supabase network traffic. If capture ever fails, set SUPABASE_ANON_KEY (safe to expose) and re-run.

Environment variables

Variable

Required

Mode

Purpose

TCM_BASE_URL

no (defaults to production)

all

Base URL of the TCM instance. Defaults to https://tcm-ochre.vercel.app; set only to point at a preview / self-hosted instance.

TCM_SESSION_FILE

no

refreshing

Override the session-file path (default ~/.tcm-mcp/session.json).

TCM_BROWSER_PROFILE

no

refreshing

Override the login browser-profile dir (default ~/.tcm-mcp/browser).

TCM_USER_TOKEN

one credential

static

User's Supabase JWT (legacy; expires ~1h, no refresh).

CLUTCH_API_KEY

one credential

headless

Server-to-server key; must match TCM's CLUTCH_API_KEY.

MCP_AGENT_USER_ID

yes, in headless mode for writes

headless

profiles.id UUID of the Clutch Agent service profile, for write attribution.

The recommended credential is the login session file (npm run login), not TCM_USER_TOKEN — see Auto-refreshing login. TCM_USER_TOKEN remains for CI / scripts that already have a JWT.

The write safety flow (dry-run → approval → commit)

create_test_case and update_test_case are two-pass:

  1. Call with dry_run: true first. The tool validates, resolves IDs, and returns a summary (create: the proposed case; update: a field-level diff + before/after steps). No write happens.

  2. A human reviews and approves — Torque relays the summary to Slack via Clutch; Claude Code shows it inline in the chat.

  3. Call again with dry_run: false (or omit dry_run) to commit.

The server does not technically enforce that a dry-run/approval happened before a commit (decided: PRD OQ-4 Option A) — it's a process convention. Don't call with dry_run: false without human approval.

Local development

git clone https://github.com/JoinFullStackDev/tcm-mcp && cd tcm-mcp
npm install                 # runs prepare → tsc → dist/
npm run build               # rebuild after changes

# run the stdio server directly (Ctrl-D / EOF to exit)
TCM_BASE_URL=https://your-tcm-instance.example.com \
TCM_USER_TOKEN=your-jwt \
node dist/index.js

npm run dev                 # same, via ts-node (no build step)

Startup logs (mode, base URL, "Ready") are written to stderr, so they don't interfere with the stdio MCP protocol on stdout.

Notes & caveats

  • Audit logging (mcp_tool_calls, PRD Appendix C) requires migration 00042 applied to the TCM database. The log inserts are fire-and-forget and non-blocking — if the table is missing, tools still work; only the audit trail is skipped.

  • Distribution is git-URL only (no npm publish). Pin a tag; ensure hosts have git access.

  • The --stdio arg in the config is cosmetic — stdio is the only transport.

Available Tools

5 tools
create_test_caseA

Create a test case with steps. REQUIRED: call with dry_run: true first. Review the summary with a human. Only call with dry_run: false (or omit dry_run) after explicit human approval. Steps are required. display_id is assigned by TCM on commit.

ParametersJSON Schema
NameRequiredDescriptionDefault
tagsNoFree-form tags (each ≤50 chars).
stepsYesTest steps (required; step_number assigned by order, 1-based).
titleYesTest case title (1–500 chars).
dry_runNotrue → validate + return summary to caller, no write. false/omit → commit (only after human approval of a dry-run).
priorityNoPriority (v1: low/medium/high only; critical deferred to v2).
suite_idYesSuite UUID (from search_suite).
descriptionNoDescription text (optional).
preconditionNoPrecondition text (optional).
platform_tagsNoPlatform tags (constrained enum: desktop/tablet/mobile only).
automation_statusNoDefault: not_automated.

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well by disclosing the dry-run validation vs. commit behavior, the requirement for human approval, and that display_id is assigned by TCM on commit. It stops short of describing validation failures or side effects, but the key behaviors are transparent.

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

Conciseness5/5

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

The description is three sentences and front-loaded with the primary verb and resource. The REQUIRED dry-run workflow is stated in a deliberate, direct manner without any extraneous content. Every sentence contributes essential operational guidance.

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 10-parameter tool with 3 required parameters and no output schema, the description covers the critical workflow and key constraints (steps required, dry_run first, display_id on commit). It doesn't explain the return value or failure modes, but the rich schema and concise workflow guidance make the tool usable; a small gap remains regarding what the dry-run summary contains and follow-up actions on validation failure.

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

Parameters3/5

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

Schema description coverage is 100%, so the input schema fully documents all 10 parameters. The description adds no new parameter details beyond reinforcing that steps are required (already in schema) and noting that display_id is assigned on commit (a behavioral outcome, not a parameter semantic). Baseline 3 is appropriate given complete schema coverage.

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 opens with 'Create a test case with steps,' which uses a specific verb and resource, clearly distinguishing this creation tool from sibling tools like update_test_case, get_test_case, and search_suite. The added step requirement and commit workflow reinforce its unique purpose.

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?

The description provides explicit instructions on when to use dry_run true (first), when to get human approval, and when to commit with dry_run false/omitted. However, it does not explicitly compare against sibling tools or state when not to use this tool at all, so it falls short of a 5.

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

get_test_caseA

Get full detail of a test case by display_id (e.g. "APA-3"), including all steps. Use this before update_test_case to review the current state.

ParametersJSON Schema
NameRequiredDescriptionDefault
display_idYesHuman-readable test case ID, e.g. "APA-3".

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the burden. 'Get' implies a read-only operation, and it mentions returning full detail with all steps. However, it does not explicitly state safety (no side effects) or error behavior, leaving some ambiguity.

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

Conciseness5/5

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

Two concise sentences: first states the primary function, second provides a concrete usage guideline. No wasted words.

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

Completeness5/5

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

Given the simple single-parameter tool with no output schema, the description adequately explains what is returned (full detail, all steps), how to identify the test case, and when to use it. No additional documentation is necessary.

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

Parameters3/5

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

Schema coverage is 100%, providing full parameter documentation. The description adds a usage example ("APA-3") and implies the parameter's role in retrieval, but does not significantly extend beyond the schema.

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 clearly states the tool gets full detail of a test case by display_id, including all steps. It distinguishes itself from siblings like update_test_case by implying a read-only retrieval operation.

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?

Explicitly advises using this tool before update_test_case to review current state, giving a clear use case. It does not mention exclusions for other siblings like list_test_cases, but the context is specific.

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

list_test_casesA

List test cases with lightweight projection (display_id, title, automation_status, priority). Filterable by project, suite, or search term. Default limit 50, max 200.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 50, max 200).
searchNoilike match on display_id or title.
suite_idNoFilter by suite UUID.
project_idNoFilter by project UUID (joins through suite).

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the lightweight projection fields and the default/max limit, which are useful behavioral insights. It does not explicitly state the return shape or read-only nature, but the verb 'List' and the projection list make these reasonably clear.

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

Conciseness5/5

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

The description is two sentences and front-loads the core purpose. Every sentence adds functional value: projection, filters, and limit behavior. No wasted words.

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 list tool with 4 optional parameters and no output schema, the description covers the essentials: what is returned (lightweight fields), how to filter, and result limits. It does not mention sorting or pagination, but given the max limit of 200, this is likely acceptable.

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

Parameters3/5

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

The input schema covers 100% of parameters, so the baseline is 3. The description's mention of 'filterable by project, suite, or search term' provides a useful summary but does not add new semantics beyond what the schema already states (e.g., ilike matching, UUIDs).

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 uses a specific verb and resource ('List test cases') and clearly distinguishes this tool from siblings by mentioning 'lightweight projection' and the specific fields returned. This differentiates it from get_test_case (single, detailed) and search_suite (searches suites).

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?

The description provides clear context for when to use the tool—when you need a filtered, lightweight list of test cases—and mentions the filterable dimensions (project, suite, search). However, it does not explicitly name alternative tools or state exclusions, such as 'for full details use get_test_case', so it is strong but not a 5.

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

search_suiteA

Resolve a suite name or prefix to a suite reference. Call this before create_test_case or list_test_cases to get the suite_id. Returns all matches so the caller can disambiguate if >1.

ParametersJSON Schema
NameRequiredDescriptionDefault
project_idYesProject UUID. Scopes the search (prefix is only unique per project).
name_or_prefixYesSuite name or prefix to search (case-insensitive, substring match).

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description must disclose behavioral traits. It reveals that 'Returns all matches so the caller can disambiguate if >1', which is important. However, it does not describe the return structure, error behavior, or required permissions, leaving gaps for a tool with no output schema.

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

Conciseness5/5

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

Three concise sentences front-load the purpose, provide usage context, and note a key behavioral detail. Every sentence contributes value without redundancy.

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?

The description covers the tool's purpose and usage, and mentions that it returns matches and yields a suite_id. However, with no output schema and no annotations, it stops short of fully describing the return format and edge cases, making it slightly incomplete.

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

Parameters3/5

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

Schema description coverage is 100%, with both project_id and name_or_prefix well described. The description adds no parameter-specific meaning beyond the schema, so the baseline of 3 applies.

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 clearly specifies the verb 'Resolve' and resource 'suite name or prefix' with an output of 'suite reference'. It distinguishes itself from siblings by positioning as a prerequisite lookup for create_test_case and list_test_cases.

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?

The description explicitly instructs when to use the tool: 'Call this before create_test_case or list_test_cases to get the suite_id.' This is clear, though it does not mention when not to use it or direct alternatives.

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

update_test_caseA

Partially update an existing test case by display_id. If steps is provided, ALL existing steps are wiped and replaced (full-replace — not partial). REQUIRED: call with dry_run: true first. The dry-run shows the full before/after diff including steps. Only call with dry_run: false after explicit human approval.

ParametersJSON Schema
NameRequiredDescriptionDefault
tagsNoNew tags (optional, replaces all).
stepsNoIf provided: FULL REPLACE of ALL steps. Omit to leave steps unchanged.
titleNoNew title (optional).
dry_runNotrue → compute diff + return to caller, no write. false/omit → commit (only after human approval).
priorityNoNew priority (optional).
display_idYesTarget test case display_id, e.g. "APA-3".
descriptionNoNew description (optional).
preconditionNoNew precondition (optional).
platform_tagsNoNew platform tags (optional, replaces all).
automation_statusNoNew automation status (optional).

TDQS

A4.8/5.0
Behavior5/5

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

No annotations are provided, so the description carries full responsibility. It discloses a critical destructive behavior: 'ALL existing steps are wiped and replaced (full-replace — not partial)' and mandates a dry-run first for safety. This goes beyond a generic update description and alerts the agent to the mutating consequence.

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

Conciseness5/5

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

Three sentences, tightly packed. The purpose is front-loaded, followed by the two most critical safety warnings. Every sentence earns its place with zero filler.

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 tool with 10 parameters, no annotations, and no output schema, the description covers the essential workflow and the most dangerous edge case (steps replacement). It doesn't mention that tags and platform_tags also replace-all, but the schema already documents those semantics, so the description is not incomplete. It could briefly note other replace-all fields but is otherwise adequate.

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 input schema has 100% description coverage, so baseline is 3. The description adds value by emphasizing 'by display_id', repeating the steps full-replace warning, and explaining that dry-run shows 'the full before/after diff including steps' — a detail not in the schema. This is a modest but meaningful addition.

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 clearly states 'Partially update an existing test case by display_id', using a specific verb ('update') and resource ('test case') and key parameter. It distinguishes from sibling tools like create_test_case (create) and get_test_case (read), making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly requires 'call with dry_run: true first' and 'Only call with dry_run: false after explicit human approval', providing a clear mandatory workflow. It also clarifies the full-replace behavior for steps, giving the agent precise conditions for safe use.

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. Dates show when Glama detected each change.

  1. 5 tool updatesv1.0.0
    • First observedcreate_test_case
    • First observedget_test_case
    • First observedlist_test_cases
    • First observedsearch_suite
    • First observedupdate_test_case
Install Server
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TDQS

A4.3/5.0
Disambiguation5/5

Each tool has a distinct purpose: create, update, get, list, and suite search. No two tools overlap in function, and search_suite clearly serves as a helper for resolving suite IDs before other operations.

Naming Consistency5/5

All tools use a verb_noun snake_case pattern (create_, update_, get_, list_, search_). The only deviation is list_test_cases using plural while others use singular, which is a standard convention for list operations.

Tool Count5/5

Five tools is well-scoped for a test case management server. Each tool covers a necessary operation without redundancy or bloat.

Completeness3/5

Core CRUD operations are present (create, get, update, list), but delete_test_case is missing. Suite management is limited to search, with no create/update/delete for suites, leaving notable lifecycle gaps.

Maintenance

ActivityMaintained
ResponsivenessResponsive

Resources

Unclaimed servers have limited discoverability.

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