gapup-mcp

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

Name	Required	Description
`data`	Yes	Payload 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}.
`mode`	Yes	Action to perform in the CRM
`async`	No	If 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.
`provider`	Yes	CRM provider to target
`credentials`	No	Auth credentials. HubSpot: access_token. Salesforce: access_token + base_url. Pipedrive: api_key.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`url`	No
`mode`	Yes
`status`	Yes
`signals`	Yes
`sources`	Yes
`success`	Yes
`provider`	Yes
`data_synced`	No
`resource_id`	No
`quality_score`	Yes

TDQS

A4/5.0

Behavior5/5

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

The description discloses important behavioral traits: it returns a mock result with a warning signal when credentials are absent, details authentication requirements per provider, and outlines return values (resource_id, CRM URL, signals, quality_score). This adds significant context beyond the annotations, which only indicate readOnlyHint=false and openWorldHint=true.

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 concise and front-loaded with the main action. Each sentence adds value, covering modes, return values, fallback behavior, and auth. It could be more structured with bullet points, but it remains efficient and scannable.

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 (multiple providers, four modes, async option, auth variations), the description covers all critical aspects: mode actions, provider options, auth details, fallback behavior, return values, and async usage. It is comprehensive and leaves no obvious gaps.

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% with all parameters described. The description adds a summary of payload structures per mode, which is helpful but does not provide new semantics 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 clearly states the tool's purpose: push, update, search, and log activities in HubSpot, Salesforce, or Pipedrive. It enumerates four modes with specific actions, leaving no ambiguity about what the tool does. Given the extensive sibling list with no direct competitors, the purpose is well-differentiated.

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

Usage Guidelines2/5

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

The description does not provide explicit guidance on when to use this tool versus alternatives. It does not mention exclusions or alternative tools for similar tasks. Usage is implied through mode descriptions but not stated, limiting the agent's ability to decide appropriately.

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

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources

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