Skip to main content
Glama

apis_io_search

START HERE. Federated overview of the APIs.io catalog for a query: the top matching APIs, providers, AND tags in one call, each with its total match count. Filter by tags, artifact types, industry, region, rating band. limit is per section. To page/sort the full list of ONE type, use find_apis / find_providers / find_tags; for one entity, get_api / get_provider.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFree text over name + description.
areaNo
bandNoRating bands: exemplar, strong, developing, thin, minimal.
sortNoOrder results. Default: relevance with a query, composite (quality) when browsing. `demand` = Fortune-1000 adoption, scoped to the query.
tagsNoTag slugs.
limitNoTop matches to return per section (apis/providers/tags).
matchNoany
regionNo
contextNoOptional: why you are asking. One sentence — the task you are trying to complete, or what you expect to get back. Never included in the answer and never used to rank; it is read only when a result turns out to be wrong, which is when knowing the intent is what makes the report actionable.
industryNo
min_scoreNo
providersNo
artifact_typesNo

TDQS

A4.4/5.0
Behavior4/5

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

Without annotations, the description carries the burden. It discloses that the tool returns federated overview with per-section limits, filters, and match counts, which covers the key behavior. It does not state read-only explicitly, but the nature of a search tool and the lack of mutation hints make this a minor gap. Given the absence of annotations, this is a strong and informative disclosure.

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?

Two sentences with zero redundancy. The primary use case and alternatives are front-loaded, and every phrase earns its place. The 'START HERE' marker is an efficient navigation cue.

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?

For a search-overview tool with 13 optional parameters, the description provides a clear summary of purpose and distinguishes it from related tools. It does not detail the return structure, but that is not necessary for this tool's scope. Some parameter semantics are left to the schema, which already covers key options like sort, tags, and limit. Overall, it gives enough context for correct invocation.

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 46%, so the description must compensate. It mentions filter categories (tags, artifact types, industry, region, rating band) and notes that limit is per section, adding value over the schema. However, it does not clarify parameters like q, area, match, min_score, or providers, leaving some ambiguity. The description adds moderate value but does not fully compensate for the coverage gap.

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 specific purpose: a federated overview returning top APIs, providers, and tags with match counts. It explicitly distinguishes itself from sibling tools (find_apis, find_providers, find_tags, get_api, get_provider), making its role unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It opens with 'START HERE' and explicitly tells when NOT to use it: 'To page/sort the full list of ONE type, use find_apis / find_providers / find_tags; for one entity, get_api / get_provider.' This gives clear context to the agent and prevents mis-selection.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.1/5.0
Disambiguation3/5

Most tools are clearly separated by artifact type or resource (find_mcp vs find_openapi vs get_provider vs get_api), but the sheer volume creates some genuinely confusable clusters: apis_io_search vs find_apis vs find_artifacts, and insights_adoption vs insights_dimensions vs find_company_insights. Several readiness-related tools (what_can_i_fix, simulate_fixes, readiness_gates) also share a conceptual boundary, though their descriptions do help.

Naming Consistency3/5

The dominant patterns (find_*, get_*, cohort_*, compare_*) are consistent and predictable, but the set mixes in irregular names like apis_io_search, tag_group_tags, what_can_i_fix, whats_changed, and resolve. These deviations are readable but break the otherwise regular verb_noun convention.

Tool Count2/5

106 tools is far beyond the typical well-scoped server and will impose a heavy selection burden on agents. The server covers a genuinely broad domain (catalog search, ratings, cohorts, agent readiness, lists, exports, feedback), so the count is defensible in scope, but it is still too many to navigate efficiently.

Completeness5/5

The surface is remarkably complete: search and browse, single-entity detail, comparisons, cohort analytics, agent-readiness assessment, saved searches, list management, feedback/correction flows, and full dataset exports are all covered. There are no obvious dead ends, and even minor operations like re-running saved searches or simulating fixes are present.

Resources