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teams-chat-mcp

teams-chat-mcp

by hanshengcc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

search_messages

Read-only

Find message text and subjects across your Microsoft Teams conversations, filtering by date, limit, or conversation name to locate relevant chats and posts.

Instructions

Search message text and subjects across the user's Teams conversations.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_messages"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax matches to return (1-1000)
queryYesCase-insensitive regex or plain text
sinceNoStart date, default 90 days ago
conversation_matchNoOnly conversations whose name contains this

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds the search scope (message text and subjects) but says nothing about result ordering, pagination, rate limits, or the cost of broad regex queries.

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?

A single, front-loaded sentence with no filler. Every word carries meaning and the scope qualifier is attached directly to the action.

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 simple search tool with full schema coverage, an output schema, and annotations covering safety, the description is nearly sufficient. Its only shortfall is routing guidance relative to get_messages, which overlaps this tool's territory.

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 limit, query, since, and conversation_match are already fully documented in the schema. The description adds no syntax, defaulting, or matching-behavior detail beyond what the schema provides, making the baseline 3 appropriate.

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?

States a specific verb (search) and resource (message text and subjects), scoped to the user's Teams conversations. It is clearly distinct from list_conversations and draft_message, but it never explicitly contrasts itself with the closest sibling, get_messages.

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 gives no when-to-use guidance, no prerequisites, and no indication of when a plain retrieval tool like get_messages is preferable. Usage is only inferable from the verb 'search'.

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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