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Glean MCP Server

Glean MCP Server

by gleanwork
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Glean Local MCP Server Monorepo

IMPORTANT

This repository is archived / no longer maintained.

Do not use this repository for new MCP setups. It predates Glean’s managed remote MCP server and is no longer the supported path for connecting MCP-compatible hosts to Glean.

What to use instead

Use the managed Glean MCP server built into your Glean instance:

For local command-line workflows, use Glean CLI instead of this local MCP server.

Related MCP server: MCP Boilerplate

Repository status

This repository is retained for historical reference only. Issues and pull requests have been closed as part of archival cleanup, and no new feature work or bug fixes are planned here.

The local packages in this repository should not be used for new installations. Published user-facing local MCP packages are being retired in favor of the managed Glean MCP server.

What this repository used to contain

This monorepo previously contained packages for running and supporting a local stdio-based MCP server for Glean:

  • @gleanwork/local-mcp-server — a local MCP server that exposed Glean Search, Chat, People Search, and document-reading tools.

  • @gleanwork/mcp-server-utils — shared utilities used by the local MCP server packages.

These packages predate the managed remote MCP server and are no longer the recommended or supported MCP integration path.

Historical reference

Existing install, Docker, and client-configuration instructions have intentionally been removed from the main documentation so new users are not directed toward an unsupported setup. If you need to understand the old implementation, inspect the repository history.

License

MIT License — see the LICENSE file for details.

Available Tools

3 tools
chatC

Chat with Glean Assistant using Glean's RAG

    Example request:

    {
        "message": "What are the company holidays this year?",
        "context": [
            "Hello, I need some information about time off.",
            "I'm planning my vacation for next year."
        ]
    }

Inputs: message (required), context.

company_searchC

Find relevant company documents and data

    Example request:

    {
        "query": "What are the company holidays this year?",
        "datasources": ["drive", "confluence"]
    }

Inputs: query (required), datasources.

people_profile_searchC

Search for people profiles in the company

    Example request:

    {
        "query": "Find people named John Doe",
        "filters": {
            "department": "Engineering",
            "city": "San Francisco"
        },
        "pageSize": 10
    }

Inputs: filters, pageSize, query.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: 'chat' is for conversational interaction with an assistant, 'company_search' is for finding documents and data, and 'people_profile_search' is for locating employee profiles. There is no overlap in functionality, making it easy for an agent to select the correct tool based on the task.

    Naming Consistency4/5

    The tool names follow a consistent snake_case pattern and are descriptive, but there is a minor deviation: 'chat' uses a simple verb, while the other two tools use a noun_noun structure (e.g., 'company_search'). This slight inconsistency does not hinder readability or predictability significantly.

    Tool Count3/5

    With only 3 tools, the set feels thin for a server named 'Glean MCP Server', which implies broader capabilities in information retrieval and assistance. While the tools cover chat, document search, and people search, the scope might benefit from additional tools for more granular operations or updates, making the count borderline appropriate.

    Completeness3/5

    The tools provide basic search and chat functionalities, but there are notable gaps. For example, there is no tool for updating or managing data (e.g., creating documents or modifying profiles), and the chat tool lacks explicit support for follow-up actions or context persistence. This limits the server's ability to handle full lifecycle operations in its domain.

    Maintenance

    ActivityNo data
    ResponsivenessOutdated data

    Resources

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