TENEKS MCP

List TENEKS recordings

list_conversations

Read-onlyIdempotent

List the user's recordings, newest first, with optional filters.

Returns metadata only -- no transcript text. Use get_transcript with a
conversation_id from here to read what was actually said.

A filter that matches nothing in this workspace is reported in
unmatched_filters and ignored rather than returning an empty list, so a
misspelled name does not look like an absence of calls.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_conversations"
  }
}

Input Schema

Name	Required	Description
`limit`	No	How many to return.
`offset`	No	Skip this many.
`rep_id`	No	Only this rep's calls, selected by id from describe_workspace. Use when two people share a name. Takes precedence over rep_name.
`date_to`	No	ISO date, inclusive.
`rep_name`	No	Only this rep's calls. Use a name from describe_workspace.
`call_type`	No	Only this call type. Use a label from describe_workspace.
`date_from`	No	ISO date, inclusive. e.g. 2026-08-01

Output Schema

Name	Required	Description
`offset`	Yes
`has_more`	Yes
`conversations`	Yes
`total_matching`	Yes	Total matching the filters, ignoring paging.
`unmatched_filters`	No	Filters that matched nothing in this workspace. The results ignore them, so treat the list as answering a broader question than asked.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 4, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses the sort order, that results are metadata-only with no transcript text, and the non-obvious quirk that non-matching filters land in unmatched_filters instead of yielding an empty list. That last point is exactly the kind of behavior an agent would otherwise misread as "no calls exist".

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 primary action is stated first, followed by the return-scope note, then the filter caveat. Three short paragraphs, each carrying distinct information, with no restatement of the name or title.

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?

Seven optional parameters, full schema descriptions, an output schema, and complete safety annotations mean the description only needs to cover ordering, filter edge behavior, and the next step, and it does all three. Nothing an agent needs to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning to the filter parameters by explaining their failure mode (an unmatched filter is reported and ignored rather than silently returning nothing). It adds nothing for limit/offset, which the schema already covers with defaults and bounds.

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?

"List the user's recordings, newest first, with optional filters" gives a specific verb (list), resource (recordings), ordering, and scope. The second sentence routes transcript reading to get_transcript, so an agent can separate this tool from its closest sibling without opening the schema.

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?

It explicitly names the alternative for the follow-up step (get_transcript with a conversation_id from here), which is the main fork an agent faces after listing. It does not say when ask_teneks or describe_workspace would be preferred instead, so the guidance is clear but not exhaustive.

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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