gapup-mcp

partnership_synergies

Read-onlyIdempotent

Identify and rank strategic partnership opportunities for a company. Returns 5-12 high-fit partnership targets, each scored on revenue lift, time-to-impact, integration complexity and regulatory risk, with a rationale and a recommended first-step outreach playbook. When to use this tool: the user wants business-development or alliance ideas, or M&A target screening before deeper due diligence. Inputs: the user's own company and the strategic axis to unlock through partnership (e.g. enter a new market via distribution, add AI infrastructure without rebuilding). Delivered by Antoine, the AI CSO of the Gapup portfolio.

Input Schema

TableJSON Schema

Name	Required	Description
`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.
`focus`	No
`constraints`	No
`selfCompany`	Yes
`strategicAxis`	Yes	What strategic axis to unlock through partnership (e.g. 'enter US market via distribution', 'leverage AI infra without rebuild')
`currentPartnerships`	No	Existing alliances to factor in

Output Schema

TableJSON Schema

Name	Required	Description
`kpis`	No	3-5 headline KPI bubbles
`sources`	No
`recommendations`	No	Prioritised next steps
`executiveSummary`	Yes	Board-ready partnership opportunity overview
`partnershipTargets`	Yes	5-12 ranked partnership targets

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the bar is lowered. The description adds behavioral context by detailing the output structure (scored dimensions, rationale, playbook) and mentions the delivering persona. It does not contradict annotations.

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?

The description is concise and front-loaded with the core purpose, followed by output, usage, inputs, and persona. Every sentence contributes value without redundancy.

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?

Given the tool's complexity (6 params, nested objects, output schema), the description provides a clear overview of what it returns and when to use. It covers the strategic context and inputs adequately. Could be enhanced by mentioning data sources or company scope, but overall sufficient.

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 50%, and the description adds meaning for key parameters: it explains 'strategicAxis' with examples and mentions the company input. However, it does not fully compensate for the low coverage by detailing all parameters or their interactions.

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 with specific verb 'Identify and rank' and resource 'strategic partnership opportunities'. It distinguishes itself from sibling tools by explicitly stating when to use it (business-development/alliance ideas, M&A pre-screening) and implies alternative tools for deeper due diligence.

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 usage scenarios: 'When to use this tool: the user wants business-development or alliance ideas, or M&A target screening before deeper due diligence.' It lacks explicit 'when not to use' statements but the context with sibling tools like ma_deal_screener provides implicit guidance.

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.

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