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djmoore-projects

HubSpot MCP Server

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.1

  • Disambiguation5/5

    Each tool targets a distinct operation: creating/updating a contact, looking up a contact by email, logging an activity on a contact, and searching companies. No ambiguity between tool purposes.

    Naming Consistency5/5

    All tools follow a consistent 'hubspot_verb_noun' pattern (e.g., hubspot_create_contact, hubspot_get_contact). The naming is uniform and predictable.

    Tool Count5/5

    With 4 tools covering core CRM operations (contact CRUD via upsert, activity logging, company search), the count is well-scoped for a focused integration.

    Completeness4/5

    The set covers essential contact operations (create/upsert, retrieve) and adds activity logging and company search. Missing explicit update or delete tools, but upsert mitigates the gap. Minor missing features like company detail retrieval prevent a perfect score.

  • Average 3.6/5 across 4 of 4 tools scored.

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

    • No community issues in the last 6 months
    • 3 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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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

  • Behavior2/5

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

    No annotations provided, so the description carries full burden. It states 'Log' which implies a write operation, but does not disclose any side effects, permissions required, or limitations. The description is minimal and adds little beyond the parameter schema.

    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?

    The description is a single sentence of 12 words, efficiently stating the purpose. It is front-loaded and contains no unnecessary information. Could be improved by adding brief usage context, but it is appropriately sized for a simple tool.

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

    Completeness3/5

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

    For a tool with 3 parameters all described and no output schema, the description is minimal. It does not explain what the tool returns, error conditions, or caveats. While sufficient for basic understanding, it lacks completeness for complex use cases.

    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 schema already explains each parameter. The description adds no extra meaning beyond listing activity types. Baseline score of 3 is appropriate as the description does not harm but adds negligible value.

    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 clearly states the tool logs an engagement (note, email, or call) on a contact's HubSpot timeline. It uses a specific verb 'Log' and identifies the resource. However, it does not differentiate from sibling tools, but siblings are distinct in function.

    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?

    No explicit guidance on when to use this tool versus alternatives. The context implies it should be used to log activities on contacts, but lacks exclusions or conditions. Sibling tools are different enough that confusion is unlikely, but guidance would improve usability.

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

  • Behavior2/5

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

    No annotations exist, so the description should fully disclose behavior. It only lists returned fields, omitting error handling, idempotency, or side effects. Missing transparency on what happens if email is not found.

    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 front-load the core action and return fields, with no redundant or extraneous content.

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

    Completeness3/5

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

    Description covers purpose and return fields but lacks output schema and details on error behavior or edge cases. Adequate for a simple lookup but incomplete for robust agent use.

    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% and describes the email parameter. The description's phrase 'by email address' is redundant. No additional semantics beyond schema are provided.

    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 specific verb 'Look up' and resource 'HubSpot contact by email address', clearly distinguishing from sibling tools like hubspot_create_contact (create) and hubspot_search_companies (search).

    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?

    No explicit when/when-not-to-use guidance is provided. The context implies usage when needing contact details by email, but does not mention alternatives or exclusions like creating contacts.

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

  • Behavior3/5

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

    No annotations provided; the description correctly discloses the upsert behavior but omits other behavioral traits like rate limits, required permissions, or return values.

    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?

    One sentence clearly states the core functionality with no unnecessary words. Front-loaded and efficient.

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

    Completeness3/5

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

    The description is minimal and does not mention return behavior or provide guidance on sibling tools. For a simple tool this is acceptable but could be more complete.

    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 descriptions cover all parameters (100%), so the description adds no new meaning beyond reiterating the email as unique key. 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 clearly states the tool creates or updates a HubSpot contact based on email. It distinguishes from siblings like hubspot_get_contact (read) and hubspot_search_companies (search).

    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?

    The description implies usage for create/update by email but lacks explicit guidance on when to use this vs alternatives like hubspot_get_contact for reading.

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

  • Behavior3/5

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

    No annotations provided, so description carries full burden. It describes a straightforward search operation without side effects. However, it does not disclose behavior like pagination, exact match vs fuzzy search, or authentication requirements. Adequate for simple use.

    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?

    One concise sentence that front-loads the purpose and outcome. No redundant information. Every word adds value.

    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 tool with one parameter and no output schema, description covers what it searches and returns. Minor gap: does not mention if results are limited or paginated, but overall sufficiently complete for intended use.

    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% for the single 'query' parameter, so baseline is 3. Description adds minimal value beyond schema by stating search by name or domain, but essentially restates the schema description. No additional format or constraints.

    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?

    Description clearly states the tool searches HubSpot companies by name or domain and returns matching names/domains. 'Search' is a specific verb, resource is 'HubSpot companies', and output is described. Distinguished from sibling tools which deal with contacts and activities.

    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?

    No explicit guidance on when to use this tool versus alternatives. However, the sibling tools are for different resources (contacts, activities), so usage context is implied but not stated. Lacks indication of limitations or when not to use.

    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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