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Glean Developer Platform

Experimental

Introducing Glean Platform APIs

Build search experiences and run Glean agents in your applications with our new Platform APIs — now rolling out in experimental preview.

Explore Platform APIs

Chat API

Chat grounded in company knowledge

Ask across every connected app and get permission-aware answers, with citations, in a single API call.

Search API

Search your entire knowledge graph

Enterprise search over 100+ connected sources — ranked, permission-aware, and fast, from one query.

Agents

Build agents on your company's knowledge

Plan, retrieve, and act across your tools — agents reason over the knowledge graph, not just a prompt window.

Web SDK

Embed Glean in your apps

Drop permission-aware search and chat into the tools your team already uses — one npm package, two components.

Indexing SDK

Bring any data into Glean

Build a connector on the open-source indexing SDK — push documents from any source and make them searchable everywhere.

Start buildingAPI reference

chat.pyChat API

from glean.api_client import Glean

with Glean(
    api_token=os.environ["GLEAN_API_TOKEN"],
    server_url=os.environ["GLEAN_SERVER_URL"],
) as client:
    response = client.client.chat.create(
        messages=[{"fragments":
            [{"text": "Summarize the Q3 roadmap"}]}]
    )
    answer = "".join(
        f.text or ""
        for m in response.messages or []
        for f in m.fragments or []
    )

search.pySearch API

from glean.api_client import Glean

with Glean(
    api_token=os.environ["GLEAN_API_TOKEN"],
    server_url=os.environ["GLEAN_SERVER_URL"],
) as glean:
    results = glean.client.search.query(
        query="quarterly reports",
        page_size=10,
    )
    titles = [r.title for r in results.results]

agent.pyAgents

from glean.agent_toolkit.tools import (
    search,
    employee_search,
)

# Use with LangChain
search_tool = search.as_langchain_tool()
people_tool = employee_search.as_langchain_tool()

# Use with CrewAI
crew_tool = search.as_crewai_tool()

embed.tsWeb SDK

import {
  renderSearchBox,
  renderSearchResults,
  renderChat,
} from "@gleanwork/web-sdk";

renderSearchBox(searchEl, {
  backend: "https://acme-be.glean.com",
  onSearch: (query) =>
    renderSearchResults(resultsEl, { query }),
});

renderChat(chatEl, {
  backend: "https://acme-be.glean.com",
});

connector.pyIndexing SDK

from glean.indexing.connectors import (
    BaseDatasourceConnector,
)

class CatalogConnector(BaseDatasourceConnector):
    def get_data(self):
        return load_catalog_pages()

connector = CatalogConnector(name="catalog")
connector.index_data(mode=IndexingMode.FULL)

Choose your path

Four ways to get started.

Build with the APIsSearch, chat, and agents from your code — with client libraries for four languages.Embed with the Web SDKPermission-aware search and chat inside the apps your team already uses.Connect your dataBring any source into Glean with the Indexing API and connector framework.Bring Glean to your IDEClaude Code, Cursor, Codex, and any MCP host.

Quickstart

One call to your knowledge graph

1. 1Create an API token in Authentication — OAuth or a Glean-issued token.
2. 2Install a client library for your language.
3. 3Run your first query — results come back ranked and permission-aware.

main.py

from glean.api_client import Glean

with Glean(
    api_token=os.environ["GLEAN_API_TOKEN"],
    server_url=os.environ["GLEAN_SERVER_URL"],
) as glean:
    results = glean.client.search.query(
        query="quarterly planning",
        page_size=10,
    )
    for r in results.results:
        print(r.title, r.url)

API client libraries

Python

TypeScript

Java

Go

Bring Glean into your IDE

Claude CodeInstall the Glean plugins and search company knowledge from your terminal.CursorConnect the Glean MCP server to Cursor for context-aware coding.CodexInstall the Glean plugin for Codex — enterprise knowledge in your terminal.

Plus GitHub Copilot, Goose, Windsurf, and any MCP host.

Agents

Framework-agnostic by design

The agent toolkit exposes Glean retrieval as tools for whatever you build with — the knowledge graph comes along regardless of framework.

LangChainOpenAI Agents SDKGoogle ADKMCP

Explore the agent toolkit

tools.pyAgent toolkit

from glean.agent_toolkit.tools import (
    search,
    employee_search,
)

# LangChain
lc_tool = search.as_langchain_tool()

# CrewAI
crew_tool = search.as_crewai_tool()