Microsoft Graph MCP Server

search_messages

Search Microsoft Teams messages using KQL queries. Specify the query and optional top count to control the number of returned results.

Instructions

Search Teams messages using Microsoft Search KQL.

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

Name	Required	Description	Default
`top`	No
`query`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 8, 2026

TDQS

C2.8/5.0

Behavior2/5

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

With no annotations provided, the description carries full responsibility for disclosing behavior. It implies a read-only search but does not mention pagination, result ordering, authorization requirements, or any operational side effects. The KQL mention adds some method transparency, but key behavioral details are absent.

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 with no redundant words or filler. It front-loads the core action and resource, making it easy to scan and understand quickly.

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

Completeness2/5

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

The description is too sparse to be fully contextual. It omits what the returned results look like, whether it covers channel messages, chat messages, or both, and any important constraints or output shape. Given many similar search tools in the sibling list, this lack of context increases the risk of selecting the wrong tool.

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

Parameters2/5

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

The schema provides only titles and defaults with no descriptions, and the tool description does not compensate. It clarifies that 'query' accepts Microsoft Search KQL syntax, but it does not explain the 'top' parameter, how it interacts with the query, or what kinds of KQL expressions are supported.

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 ('Search'), the resource ('Teams messages'), and the method ('Microsoft Search KQL'), making the primary purpose unmistakable. It does not explicitly contrast with sibling search tools like search_files or search_sites, but the resource-specific wording is enough to distinguish this tool.

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 explicit guidance on when to prefer this tool over alternatives such as search_query, people_search, or search_files. There is no indication of intended scenarios, scope limitations, or when not to use it, leaving the agent to infer usage purely from the tool name.

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

Deploy Server