HelpMyAgent

Search HelpMyAgent APIs

search_apis

Find HelpMyAgent APIs matching an agent task or intent. This tool returns discovery metadata only.

Input Schema

TableJSON Schema

Name	Required	Description
`query`	Yes	Describe the task or intent to match against the published HelpMyAgent API catalogue.
`country`	No	Optional ISO 3166-1 alpha-2 country code, for example FR.
`category`	No	Optional HelpMyAgent API category.
`max_price`	No	Optional maximum price per call in the API currency.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`apis`	Yes
`count`	Yes

Schema Changelog

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

First observedSep 6, 2026

TDQS

A4.2/5.0

Behavior4/5

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

There are no annotations, so the description carries the burden of behavioral disclosure. It explicitly discloses that the tool 'returns discovery metadata only,' which is a meaningful guarantee that it does not execute or invoke the discovered APIs. It does not mention authentication, rate limits, or pagination, but for a read-oriented discovery tool the key behavioral trait is covered.

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 two concise sentences with the core behavior front-loaded and the critical return-type caveat immediately after. Every word earns its place and there is no redundant restating of the tool name.

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 a fully documented input schema and the presence of an output schema, the description is largely sufficient for an agent to invoke the tool correctly. The only notable gap is the absence of explicit guidance on when to choose this tool over sibling discovery tools such as list_categories or describe_api.

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 the schema already documents all four parameters: query, country, category, and max_price. The description's phrase 'matching an agent task or intent' loosely aligns with the query parameter but adds no substantial meaning beyond the schema.

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 uses a specific action and resource: 'Find HelpMyAgent APIs matching an agent task or intent.' It also clarifies the tool's scope by stating it 'returns discovery metadata only,' which separates it from API execution or detail-lookup tools like describe_api.

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 gives a clear usage context: an agent should use this when it needs to find HelpMyAgent APIs relevant to a task or intent. It does not explicitly name alternatives or exclusion criteria, so it stops short of full routing guidance, but the intended use case is evident.

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

B3.3/5.0

Disambiguation3/5

Most endpoints target distinct resources, but several clusters are easy to confuse: company_fr_intelligence vs company_fr_kyb, company_fr_peers vs company_fr_competitors vs company_fr_public_contract_competitors, and company_fr_risk vs company_fr_default_score vs company_fr_payment_context. The descriptive names help, but the repetitive 'Use when' sections often restate the description rather than contrasting with nearby tools.

Naming Consistency4/5

The dominant convention is domain_fr_feature with consistent snake_case, e.g., company_fr_profile, company_fr_financials, company_fr_public_contracts, procurement_fr_search, which makes the family predictable. The three meta tools (describe_api, list_categories, search_apis) switch to a bare verb_noun style, and a few company_fr names use verbs while most use nouns, creating a minor inconsistency.

Tool Count2/5

With 30 tools, the surface exceeds the 25+ threshold and feels heavy for an agent to navigate, especially because aggregators like company_fr_intelligence and company_fr_kyb overlap with many single-purpose endpoints. The broad French-company data domain justifies a large number of endpoints, but several could be consolidated or split out to make the server more focused.

Completeness4/5

The set covers discovery, verification, profile, directors, financials, legal risk, compliance, public contracts, procurement, funding, benchmarking, signals, and aggregation, so core French-company workflows have no major dead ends. Minor gaps remain around beneficial-ownership/shareholder data and subscription-style monitoring, but those are explicitly outside the stated scope of most endpoints.

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