Agentic Endpoints

Search your meeting transcripts

meetings_search

Read-onlyIdempotent

Ask a question across every meeting you have imported as queryable, and get back ranked excerpts with the meeting they came from. This is the tool to use when the user refers to something that was said, agreed, or decided in a call -- 'what did we decide about pricing', 'who owned the migration', 'when did we say we would ship'. Returns 'searched_meetings' and 'private_meetings_skipped': meetings imported as private are encrypted and CANNOT be searched, so if searched_meetings is 0 an empty result means nothing was searched, NOT that the topic was never discussed. Use meetings_get to read a full transcript once you have found the right meeting. Costs $0.010 in USDC on Base, paid via the x402 protocol, or from a credit token — call credits_trial for free credit if you have neither.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Max results, 1-50 (default 10)
`query`	Yes	FTS5 match expression. Use quotes for phrases, e.g. "budget review". Prefer a few distinctive words over a whole sentence.
`namespace`	Yes	Isolation scope holding your meetings
`credit_token`	No	Optional. A credit token from credits_trial or /credits/buy. Supplying it pays for this call from that balance, so no x402 payment or wallet is needed.
`namespace_token`	Yes	One-time token issued by the first call that claimed this namespace. Required for every later call.

Output Schema

TableJSON Schema

Name	Required	Description
`count`	Yes	Number of matches returned
`query`	No	The match expression that was run
`status`	Yes	'ok' on a successful search
`matches`	Yes	Ranked excerpts, best first
`searched_meetings`	No	How many meetings were actually searched. If 0, an empty result means nothing was searchable, NOT that the topic was never discussed.
`private_meetings_skipped`	No	Encrypted meetings that could not be searched

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 3, 2026

TDQS

A4.7/5.0

Behavior5/5

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

The annotations already mark the tool read-only and idempotent, and the description adds substantial beyond that: private meetings are encrypted and skipped, searched_meetings=0 means nothing was searched rather than the topic never arose, and the call costs $0.010 paid via x402 or credit token. These are exactly the non-obvious behaviors an agent needs to interpret results and avoid surprise payment failures.

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?

Every sentence earns its place: purpose, use-case triggers, return-value caveat, sibling routing, and cost disclosure. It is front-loaded with what the tool does and only then adds caveats, with no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with an output schema already present, the description covers all essential operational context: ranking behavior, private-meeting exclusion, empty-result interpretation, cost, payment method, and fallback credit path. An agent has everything it needs to select, call, and interpret this tool correctly.

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 five parameters, including FTS5 match syntax, namespace/token requirements, and the optional credit_token. The description reinforces high-level usage but does not need to add parameter-level detail; baseline 3 is appropriate.

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?

States a specific verb and resource: asking a question across imported meetings and receiving ranked excerpts with the meeting source. It clearly distinguishes itself from meetings_get, which reads a full transcript, and the example queries make the search intent concrete.

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?

Explicitly states when to use this tool: whenever the user references something said, agreed, or decided in a call. It also routes to meetings_get for reading a full transcript after the right meeting is found, and warns that private meetings cannot be searched, setting correct expectations.

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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