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gapup-mcp

by io.github.getgapup

ma_arbitrage_hunter

Read-onlyIdempotent

As a CFO, identify cross-border M&A arbitrage opportunities by comparing target company valuations across different jurisdictions. Inputs include target company ticker, primary and secondary jurisdictions, and valuation metrics. Outputs include valuation gaps, FX-adjusted multiples, and jurisdiction-specific premiums/discounts. Uses real-time ECB FX rates, Yahoo Finance market data, and SEC EDGAR filings for public companies. Ideal for quick assessment of potential arbitrage in M&A scenarios.

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.
sectorNoIndustry sector for peer comparison (e.g., 'Technology')
targetTickerYesTarget company ticker symbol (e.g., 'AAPL')
valuationMetricNoValuation multiple to use for comparison
primaryJurisdictionYesPrimary jurisdiction for valuation comparison (e.g., 'US')
secondaryJurisdictionNoSecondary jurisdiction for valuation comparison (e.g., 'DE')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
fxRateNo
statusYes
sourcesNo
warningsNo
valuationGapNo
peerMultiplesNo
targetCompanyNo
primaryValuationNo
secondaryValuationNo
jurisdictionPremiumNo

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds valuable context by naming specific data sources (ECB FX rates, Yahoo Finance, SEC EDGAR) and noting applicability to public companies, which helps the agent anticipate dependencies and limitations.

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 five sentences long, with each sentence serving a clear purpose: purpose, inputs, outputs, data sources, and use case. It is front-loaded and free of fluff, though slightly longer than necessary.

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 output schema exists and the schema documents all parameters, the description is complete for an analysis tool. It covers purpose, inputs, outputs, data sources, and the specific arbitrage scenario. Minor gaps like explicit public-company-only limitation are implied rather than stated outright.

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 baseline is 3. The description groups input parameters (target ticker, primary/secondary jurisdictions, valuation metrics) but adds no additional syntax or format detail beyond what the schema already provides.

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: 'identify cross-border M&A arbitrage opportunities' using a specific verb and resource. It distinguishes itself from siblings by emphasizing cross-border valuation comparisons, FX-adjusted multiples, and jurisdiction-specific premiums/discounts.

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 clear context on when to use it (CFO quick assessment of M&A arbitrage) but does not explicitly mention alternatives like ma_deal_screener or state when not to use it. It lacks exclusionary guidance, but the scenario is well-specified.

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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