Skip to main content
Glama

gapup-mcp

by io.github.getgapup

patent_ownership_audit

Read-onlyIdempotent

Audits patent ownership for employees or contractors, identifying gaps where inventors may not have properly assigned patent rights to the company. Designed for CHROs to ensure IP compliance and mitigate legal risks. Inputs: employee/contractor names or IDs, optional date range. Outputs: list of patents, ownership status, flagged gaps, and assignment details. Sources: USPTO PatFT and EPO Espacenet public records. Keywords: patent audit, IP compliance, employee inventions, contractor agreements, CHRO.

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.
dateRangeNoOptional date range for patent filings
employeeIdsNoList of employee or contractor IDs (optional if names provided)
employeeNamesYesList of employee or contractor full names to audit

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
gapsNo
statusYes
patentsNo
sourcesNo
warningsNo

TDQS

A4.1/5.0
Behavior4/5

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

With annotations declaring readOnlyHint, openWorldHint, and idempotentHint, the description adds valuable context about sources (USPTO/EPO), outputs (patents, ownership status, flagged gaps), and the audit nature. It does not contradict annotations and provides extra detail beyond the structured metadata.

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 structured bullet-like but in prose, including purpose, audience, inputs, outputs, sources, and keywords. It is slightly longer than necessary, but every sentence adds value and it is not bloated.

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 (4 params, nested object, output schema), the description covers purpose, inputs, outputs, and data sources comprehensively. It does not explain the async param but that is covered in the schema. It is complete for an AI agent to understand and invoke the tool.

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%, so parameters are fully documented. The description mentions inputs (names/IDs, optional date range) but adds minimal detail beyond schema descriptions. It reinforces the meaning but does not significantly extend it.

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 a specific verb ('Audits') and resource ('patent ownership for employees or contractors'), and differentiates from siblings by focusing on ownership gaps and CHRO compliance. It explicitly lists inputs, outputs, and data sources, making its purpose unambiguous.

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—designed for CHROs for IP compliance and legal risk mitigation—but does not explicitly name alternative tools or when not to use this tool. It implies the use case well but lacks explicit exclusions or alternative references.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All gapup-mcp toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources