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hoklims/stacksfinder-mcp (@stacksfinder/mcp-server)

stacksfinder-mcp-server · v1.0.0 · scanned

What changed in the harness

Selection accuracy 91→93, token cost down 1%, unconfirmed writes 0%→0%.

Category breakdown

Where the score comes from.

Earned points across the four signals Gradable measures. Safety and Legibility are scored out of 30; Economics and Discoverability are scored out of 20.

01Safety

0.0 / 30

0.0 out of 30
02Legibility

23.1 / 30

23.1 out of 30
03Economics

15.7 / 20

15.7 out of 20
04Discoverability

9.4 / 20

9.4 out of 20

Highest-impact fix

Estimated gain +30 points

Add explicit identity and permission preflight tools

Expose machine-readable principal/tenant confirmation and a non-mutating permission check so agents can verify both before destructive actions.

Description evidence

Defects and rewrites.

10 defects found across the exposed tool descriptions. Suggested rewrites make purpose, inputs, boundaries, and returns easier for an agent to understand.

Tool Defect types Suggested rewrite
recommend_stack
name_restates_behavior params_unexplained no_return_description
Computes a tailored tech stack recommendation using live scoring, weighted by up to three ranked priorities (e.g. time-to-market, scalability, security) and adjusted for the given project type (e.g. saas, api, mobile-app), scale (mvp through enterprise), and optional free-text constraints (e.g. 'must-use-postgresql'). Returns the recommended technology for each category along with scores reflecting the requested priorities and constraints.
recommend_stack_demo
params_unexplained
Generates a quick, deterministic tech stack recommendation for a given project type (e.g. web-app, saas, api, e-commerce, mobile-app) and growth scale (mvp, startup, growth, enterprise). Returns the optimal technology for each category (frontend, backend, database, etc.) along with a score and grade for each pick, based on rule-based scoring rather than AI-generated guesses.
get_blueprint
no_return_description
Fetches an existing blueprint by its UUID, previously generated via the StacksFinder web UI or the create_blueprint tool. Returns the full blueprint record, including the recommended technology stack, project metadata, and generation status.
create_blueprint
params_unexplained
Creates a new tech stack blueprint for a project, matching technologies to the given project type (e.g. saas, api, e-commerce, mobile-app) and scale. projectName is an optional label used to identify the blueprint later. Blueprint generation is asynchronous: by default this tool waits for completion and returns the full blueprint; set waitForCompletion=false to get the job ID immediately for manual polling instead.
setup_api_key
no_return_description
Authenticates with your StacksFinder account and creates an API key using email/password. Returns the newly created API key value along with its ID and name — save the key immediately, as the raw value is only shown once.
list_api_keys
name_restates_behavior no_return_description
Retrieves the API keys associated with your authenticated StacksFinder account (requires a configured API key). Returns each key's ID, name, and creation date — not the raw secret value, which is only shown once at creation.
revoke_api_key
name_restates_behavior no_return_description
Permanently deactivates the specified StacksFinder API key by its UUID so it can no longer authenticate requests. This action cannot be undone. Returns a confirmation that the key was revoked.
create_api_key
no_return_description
Creates a new API key using OAuth authentication, the preferred method for ChatGPT users, and requires a Pro or Team subscription. Returns the newly created API key value along with its ID and name — the raw key is shown only once, so save it securely immediately.
get_audit_quota
no_return_description
Checks your remaining audit quota for the current month. Returns the number of audits used, the monthly limit, and the reset date for your account tier.
get_estimate_quota
no_return_description
Checks your remaining project-estimate quota for the current week and month. Returns the number of estimates used and remaining for each period, along with the applicable limits for your account tier.

Selection evidence

Confusable tool pairs.

7 pairs where similar names or overlapping descriptions may send an agent toward the wrong tool.

Tool A Tool B Confidence Why they collide
recommend_stack_demo recommend_stack high Both take projectType/scale and return a stack recommendation; a task like 'recommend a tech stack for my SaaS' doesn't indicate whether the free demo or the Pro real-time version with priorities/constraints is wanted.
setup_api_key create_api_key high Both create an API key for the account; only the auth mechanism differs (email/password vs OAuth). A generic 'create/get me an API key' request could plausibly trigger either without the agent knowing which auth context applies.
prepare_mcp_installation execute_mcp_installation medium Both are steps in the same MCP install workflow with overlapping descriptions ('generate .env-mcp' vs 'read .env-mcp'); a task phrased simply as 'install MCP servers for my project' could cause the agent to jump straight to execute_mcp_installation without first calling prepare_mcp_installation.
generate_mcp_kit prepare_mcp_installation medium Both produce MCP setup artifacts from a project context (one from a description, one from repo analysis); a vague request like 'set up MCP recommendations for my project' doesn't clarify whether the project already exists as a repo to analyze or is just being described, risking the wrong tool choice.
get_audit_quota get_estimate_quota low Both are zero-arg 'check my remaining quota' tools with nearly identical descriptions differing only in the audit vs estimate feature; a bare request like 'check my quota' without specifying which feature could be misrouted.
get_audit list_audits low A request like 'show me my audit results' is ambiguous between fetching a specific known audit (get_audit) and listing recent audits (list_audits) when the user hasn't supplied an ID.
analyze_tech compare_techs low A task like 'how does Next.js stack up against alternatives' could be read as either a single-tech deep analysis or a multi-tech comparison, though the required array vs single string params partially disambiguate.

Compare the field

One score is useful.
The evidence makes it actionable.

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