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mcp-knowledge

by io.github.getgapup

crm_connector

Push, update, search and log activities in HubSpot, Salesforce or Pipedrive. 4 modes: push_lead (create contact/lead), update_opportunity (update deal stage/amount), search_contact (lookup by email), log_activity (call/email/meeting/note). Returns resource_id, direct CRM URL, signals and quality_score. If credentials are absent, returns a mock result with a warning signal. Auth: HubSpot via Bearer access_token; Salesforce via access_token + base_url; Pipedrive via api_key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesPayload depending on mode. push_lead: {email,first_name,last_name,company,phone,job_title}. update_opportunity: {deal_id/opportunity_id,stage,amount,close_date}. search_contact: {email}. log_activity: {type,body,contact_id/person_id,subject}.
modeYesAction to perform in the CRM
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
providerYesCRM provider to target
credentialsNoAuth credentials. HubSpot: access_token. Salesforce: access_token + base_url. Pipedrive: api_key.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo
modeYes
statusYes
signalsYes
sourcesYes
successYes
providerYes
data_syncedNo
resource_idNo
quality_scoreYes

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses key behavioral traits: returns resource_id, direct CRM URL, signals, and quality_score. It details authentication requirements per provider and explains the fallback to mock results when credentials are missing. Annotations (readOnlyHint: false, openWorldHint: true) are consistent with the described behavior, and no contradictions exist.

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 fairly concise and well-structured, with the four modes clearly listed at the beginning. However, it is somewhat lengthy and could be trimmed slightly without losing clarity. The front-loading of the main functionality is effective.

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 tool's complexity (5 parameters, nested objects, 4 modes, multiple providers, and an output schema), the description is highly complete. It covers all modes, authentication requirements, parameter structures, and fallback behavior. The presence of an output schema reduces the need to explain return values, but the description still adds valuable context.

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

Parameters5/5

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

The description adds significant meaning beyond the schema by detailing the expected data payload for each mode and the credential requirements per provider. Although schema coverage is 100%, the description provides essential context for constructing correct parameters, such as the fields for push_lead and log_activity.

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's purpose: pushing, updating, searching, and logging activities in HubSpot, Salesforce, or Pipedrive. The four modes are explicitly listed and explained, distinguishing it from any sibling tools (none of which are CRM connectors).

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 guidance on when to use each mode and explains the behavior when credentials are absent (returns mock result with warning). It also mentions async usage. However, it does not explicitly state when not to use this tool or suggest alternative tools, which would improve the score.

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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TDQS

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

Resources