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arose26

zapier-discovery-mcp

by arose26
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one searches/returns apps, the other retrieves Zap templates for a given app or app pair. There is no overlap or ambiguity in what each tool does.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern: search_apps and find_zap_templates. The naming is predictable and aligned with their respective actions.

    Tool Count3/5

    With only two tools, the server feels minimal but arguably well-scoped for its stated discovery purpose. It is exactly at the borderline between 'too few' and 'appropriately lean' for the domain.

    Completeness3/5

    The core discovery workflow (search apps, then find templates for those apps) is covered, but there are noticeable gaps such as searching templates by keyword/use case or getting detailed app information. Agents can complete the basic flow but may hit dead ends for broader discovery scenarios.

  • Average 4.2/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 2 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior4/5

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

    With no annotations, the description carries the behavioral burden. It discloses that the tool returns templates with step chains and one-click create links, and that input comes from app slugs. It does not mention sorting, pagination, or failure modes, but the read-style behavior is 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?

    A single well-structured sentence front-loads the purpose, adds a motivating question, and packs in the key details about input format and output contents without waste.

    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 simple two-parameter lookup with full schema coverage, the description provides enough context about what is returned. It lacks explicit notes on default limit behavior or result ordering, but these are minor for this tool's complexity.

    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%, so the schema already documents apps and limit with defaults and ranges. The description adds a cross-reference to search_apps and example app pairs, but does not meaningfully expand 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 states a specific action — returning popular, ready-made Zap templates — and identifies the input as app slugs from search_apps. It clearly distinguishes this from searching apps by focusing on templates with step chains and one-click create links.

    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 implies the workflow: first use search_apps to get app slugs, then use this tool to find templates for those apps. It does not explicitly say when not to use it, but the single sibling's purpose is clear enough to avoid confusion.

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

  • Behavior4/5

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

    With no annotations, the description carries the full burden of disclosure. It reveals an important behavioral nuance: 'Without a query, returns the most popular apps.' It also discloses that results contain slugs usable elsewhere. It does not state return structure, auth needs, or rate limits, but for a search tool the core behavior is covered. This is above the minimum viable level.

    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 sentences with zero filler. The main purpose is front-loaded, the default behavior is stated succinctly, and the integration with find_zap_templates is included in a single clause. Every word earns its place.

    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 read-only search tool with only two optional parameters and no output schema, the description is nearly complete. It covers the purpose, default behavior, and output usage. It doesn't specify the exact response shape, but 'returned slugs' implies the necessary output field. A fully self-contained description might mention the response format, but this is sufficient for correct invocation.

    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 already describes both parameters thoroughly (limit: max results with min/max/default; query: app name to search for). Schema description coverage is 100%, so the description doesn't need to compensate. The phrase 'returned slugs' hints at the query parameter's purpose but adds little beyond the schema. Baseline 3 is appropriate.

    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 states a specific verb ('Search'), a precise resource ('Zapier's directory of 9,000+ integrated apps'), and the search method ('by name'). It also hints at the tool's role in a pipeline by mentioning 'returned slugs' with find_zap_templates, which distinguishes it from that sibling without ambiguity.

    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: it is the tool to use for discovering apps and obtaining slugs, with an explicit pointer to the sibling tool ('Use the returned slugs with find_zap_templates'). It doesn't explicitly state when not to use it, but the chaining instruction effectively communicates the workflow. No exclusions are mentioned, so it's not a 5.

    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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