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gapup-mcp

by io.github.getgapup

vendor_management

Read-only

Gestion des fournisseurs — Gapup agent-payable C-suite expertise (COO). Returns a structured, audited deliverable. Reference case: Qonto (12 fournisseurs · €2.4M/an) — €290k économies identifiées · 4 renegociations prioritaires. Inputs are validated server-side — send the documented case fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
companyYes
vendorsYes
objectivesYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

D1.8/5.0
Behavior2/5

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

Annotations declare readOnlyHint=true and openWorldHint=true. The description adds 'Returns a structured, audited deliverable' and 'Inputs are validated server-side', but it does not explain the deliverable's structure, content, or how the async parameter works. Given no output schema, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description includes a promotional reference case ('Qonto (12 fournisseurs · €2.4M/an) — €290k économies identifiées') that provides no operational value for an AI agent. The core purpose is buried in marketing, and the useful information is minimal.

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

Completeness1/5

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

This tool has a complex nested schema (company, vendors, objectives) and no output schema. The description does not explain what the tool does, what inputs are expected in detail, or what the returned deliverable looks like. It is inadequate for an agent to select and invoke it correctly.

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

Parameters1/5

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

Only the 'async' parameter has a schema description (25% coverage). The description refers to 'documented case fields' but does not elaborate on company, vendors, or objectives, nor their nested structures. This fails to compensate for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is essentially the title 'Gestion des fournisseurs' and marketing claims ('Gapup agent-payable C-suite expertise'). It does not state a specific action such as 'analyze' or 'optimize', and it does not differentiate from siblings like vendor_risk_assessor or procurement_spend_optim. The reference case hints at savings but the core function is left vague.

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?

No explicit guidance on when to use vs. alternatives. The only instruction is 'send the documented case fields', which is about invocation, not selection. There is no mention of scenarios, prerequisites, or exclusions.

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

C2.4/5.0
Disambiguation1/5

Over 50 tools share the identical template 'Gapup agent-payable C-suite expertise' with similar French descriptions and reference cases, making their boundaries indistinguishable. Clusters like competitor_intel, competitive_deep_dive, competitor_moves, competitor_profiles, competitor_pricing_radar, competitor_pricing_scrape, and competitor_recommendations heavily overlap in purpose.

Naming Consistency1/5

Names are chaotic: mix of French and English, snake_case and camelCase, verb_noun, noun, and adjective forms with no uniform pattern. Examples like 'bp_narratif', 'content_enrichment', 'ai_governance_full_report_async', and 'job_result' show no coherent naming convention.

Tool Count1/5

271 tools is far beyond any reasonable MCP server scope, creating an overwhelming selection burden for agents. This count vastly exceeds the 25+ threshold for 'too many' and makes navigation impractical.

Completeness2/5

While the server covers many business domains, it lacks lifecycle operations (e.g., no update/delete tools for the deliverables it generates) and the input specifications are vague ('documented case fields' without documentation), creating functional dead ends. The sheer breadth does not compensate for these gaps.

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