Glean Connector MCP Server

by gleanwork

Overview Schema Source Related Servers Discussions Admin

TypeScript

run_connector

Start an async execution of a Python connector and receive an execution ID to track progress.

Instructions

Start async execution of the Python connector. Returns an execution_id immediately. Poll status with inspect_execution.

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": "run_connector"
  }
}

Input Schema

Name	Required	Description	Default
`recording_id`	No	If provided, replay from this recording instead of hitting the live source
`connector_name`	No	Python class name of the connector to run	Connector

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.6.0Jul 28, 2026

TDQS

A3.5/5.0

Behavior2/5

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

No annotations provided, so description must cover behavioral traits. It mentions async execution and immediate return, but does not disclose failure behavior, prerequisites, or whether the operation is destructive. Insufficient for a tool with no annotations.

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?

Two sentences, no wasted words. Front-loaded with purpose, immediate return value, and next step.

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

Completeness3/5

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

No output schema or annotations. Description covers return value and polling suggestion, but lacks details on error handling, idempotency, or prerequisites. Adequate but with gaps.

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 coverage is 100% with descriptions for both parameters. The tool description adds no extra semantics beyond the schema, so baseline 3 is 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?

The description clearly states the tool starts an async execution of a Python connector and returns an execution_id. It distinguishes from inspect_execution by mentioning polling for status. However, it could be more specific about what a connector is, but given sibling tools, it's adequate.

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?

States immediate return and suggests polling with inspect_execution, giving a clear usage pattern. Does not explicitly mention when not to use, but the pattern is clear.

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