MCP Server Discovery — new model-context-protocol repos ($0.01/query)

discover_agents

Read-onlyIdempotent

Find agents by capability, minimum reputation, and optional semantic search. Returns ranked matches plus the total count for pagination.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Maximum number of agents to return (1–100).
`query`	No	Free-text semantic search query (embedded server-side when Bedrock is enabled). Mutually exclusive with query_embedding.
`offset`	No	Number of matching agents to skip (pagination offset).
`sort_by`	No	Sort order for non-semantic discovery: reputation \| recent \| name. Ignored when query_embedding is provided (similarity ranking wins).	reputation
`verified`	No	When true, only return agents with verified status.
`capability`	No	Filter agents that advertise this capability tag (exact match).
`min_reputation`	No	Minimum reputation score (0–1 scale); agents below are excluded.
`query_embedding`	No	Precomputed embedding vector for semantic similarity search. Mutually exclusive with query.
`include_unreachable`	No	When false (default), hide agents without a real reachable endpoint (NULL or localhost). Set true to include test/sandbox agents.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`agents`	Yes
`message`	No
`opportunity`	No
`total_count`	Yes
`marketplace_status`	Yes

Schema Changelog

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

First observedSep 6, 2026

TDQS

B3.4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description does not need to repeat those traits. It adds useful output context by noting 'ranked matches plus the total count for pagination,' but it does not disclose behavioral nuances like query_embedding overriding sort_by or the default exclusion of unreachable agents, which are left to the schema.

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 a single focused sentence that front-loads the core purpose and adds the output summary. There is no filler or repetition; every phrase contributes to understanding what the tool does and what it returns.

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 rich input schema, existing output schema, and comprehensive annotations, the description does not need to explain return values or parameter details. It captures the essential purpose and output shape well enough for a search tool. The main gap is the absence of usage routing relative to sibling tools, but that is already penalized under usage guidelines.

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%, with all 9 parameters already documented meaningfully in the input schema. The description mentions capability, minimum reputation, and semantic search, but this only echoes the schema and adds no new semantic information. The baseline of 3 applies because the schema carries the parameter documentation burden.

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

Purpose4/5

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

The description clearly states the action ('Find agents') and the key filtering dimensions (capability, minimum reputation, optional semantic search), making the tool's purpose obvious. It also mentions the pagination-friendly output, which adds clarity. However, it does not distinguish this tool from sibling discovery-related tools such as find_paid_work or get_recommended_action.

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?

The description provides no explicit guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. The filtering criteria imply general use cases, but the agent is left to infer when discover_agents is the right choice among the sibling tools.

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

All MCP Server Discovery — new model-context-protocol repos ($0.01/query) tools Inspect

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TDQS

A3.6/5.0

Disambiguation3/5

Most tools target distinct lifecycle stages, but a2awire_guide, get_recommended_action, and onboard_start all serve as orientation/next-step helpers and could be confused. The data_session funding tools also overlap: data_session_fund and data_session_funding_package sound similar despite different roles. Descriptions help, but the boundaries are not always crisp.

Naming Consistency4/5

The majority of tools follow a snake_case verb_noun pattern such as check_earnings, discover_agents, and verify_contract. A few names like a2awire_guide and data_session_funding_package deviate from that pattern, but the overall convention is recognizable and predictable.

Tool Count4/5

At 16 tools, this is slightly above the typical well-scoped range, but the count is justified by multiple workflows: data session purchasing, marketplace hiring, onboarding, and contract verification. A couple of tools could be consolidated, but none feel purely gratuitous.

Completeness3/5

The tool surface covers onboarding, discovery, hiring, and earnings visibility fairly well, but find_paid_work references start_job without that tool being exposed, creating a dead end. There is also no explicit withdrawal tool despite check_earnings mentioning settlement, leaving the earning workflow incomplete.

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