Ragie connector for AI agents

Tools your knowledge agent reaches for on Ragie, scoped per user.

CALL ANY TOOL

32 tools for RAG retrieval in Ragie: retrieve relevant chunks, ingest and update documents, read summaries, chunks, and elements, sync and pause connections, run entity-extraction instructions, and manage partitions.

ragie_connection_enabled_set

Set connection enabled

Enable or disable a connection. A disabled connection stops syncing. Returns the updated connection. Use ragie_connection_enabled_set to pause or resume syncing. Use ragie_connection_sync to run a sync now. Requires a connection id from ragie_connections_list.

Parameters

Name

Type

Required

Description

connection_id

string

Required

ID of the connection. Get it from ragie_connections_list.

enabled

boolean

Required

True to enable the connection, false to disable it.

reason

string

Optional

Optional reason for disabling the connection, recorded by Ragie.

ragie_connection_get

Get connection

ragie_connection_source_types_list

List connection source types

ragie_connection_stats_get

Get connection stats

ragie_connection_sync

Sync connection

ragie_connections_list

List connections

ragie_document_chunk_get

Get document chunk

ragie_document_chunks_list

List document chunks

ragie_document_create_from_url

Document create from url

ragie_document_create_raw

Document create raw

ragie_document_delete

Delete document

ragie_document_get

Get document

ragie_document_metadata_update

Update document metadata

ragie_document_summary_get

Get document summary

ragie_document_update_from_url

Document update from url

ragie_document_update_raw

Document update raw

ragie_documents_list

List documents

ragie_element_get

Get element

ragie_entities_list_by_document

Entities list by document

ragie_entities_list_by_instruction

Entities list by instruction

ragie_instruction_create

Create instruction

ragie_instruction_delete

Delete instruction

ragie_instruction_extraction_logs_list

List instruction extraction logs

ragie_instruction_update

Update instruction

ragie_instructions_list

List instructions

ragie_partition_create

Create partition

ragie_partition_delete

Delete partition

ragie_partition_get

Get partition

ragie_partition_update

Update partition

ragie_retrieve

Retrieve

For more tools, view docs.

Build your Agent

Same auth pattern across LangChain, OpenAI, Anthropic, and Google ADK.

import { ScalekitClient } from "@scalekit-sdk/node";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

// Ragie tools scoped to this user
const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["ragie"], toolNames: [
    "ragie_document_create_from_url",
    "ragie_document_get",
    "ragie_retrieve"] },
  pageSize: 100,
});

const agent = createReactAgent({ llm, tools });
await agent.invoke({ messages: [{ role: "user", content: "Ingest our pricing page and search it for the enterprise plan limits" }] });

import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["ragie"] }, pageSize: 100,
});

const res = await openai.chat.completions.create({
  model: "gpt-5",
  messages: [{ role: "user", content: "Ingest our pricing page and search it for the enterprise plan limits" }],
  tools,
});

// Execute the tool call with the user's vaulted Ragie access token
await sk.tools.executeTool(res.choices[0].message.tool_calls[0], "user_123");

import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["ragie"] }, pageSize: 100,
});

const msg = await anthropic.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Ingest our pricing page and search it for the enterprise plan limits" }],
  tools,
});

// Tool call runs with the user's vaulted Ragie access token
await sk.tools.executeTool(msg.content, "user_123");

import { Agent } from "@google/adk/agents";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["ragie"] }, pageSize: 100,
});

const agent = new Agent({
  name: "knowledge_agent",
  model: "gemini-2.5-pro",
  instruction: "Ragie tools scoped to this user",
  tools,
});

await agent.run("Ingest our pricing page and search it for the enterprise plan limits");

Try these prompts

Copy any prompt into your agent. Each maps directly to a Ragie tool. Click to copy, paste into your agent, done.

Retrieve

Copy the prompt

Copied

Search our documents for the refund policy.

Copy the prompt

Copied

Summarize the Q3 board deck document.

Copy the prompt

Copied

Show the tables Ragie extracted from the pricing PDF.

Ingest and sync

Copy the prompt

Copied

Ingest our new pricing page from its URL.

Copy the prompt

Copied

Add these meeting notes as a raw text document.

Copy the prompt

Copied

Sync the Google Drive connection now.

Extraction and partitions

Copy the prompt

Copied

Create an instruction that extracts contract renewal dates from every document.

Copy the prompt

Copied

List the entities extracted from the MSA document.

Copy the prompt

Copied

Create a partition for the Acme tenant with a monthly page limit.

SEE HOW AUTH WORKS

Each user connects their own Ragie access token once, and Scalekit sends it with every call. Access tokens stay vaulted, every call is scope checked, and every action is logged.

Authorize

Your user connects

Ragie

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

Ragie

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

Ragie

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

Ragie

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

See the same per-user auth pattern across other AI and search connectors.

Support and Ops Teams

Support ticket automation agent

Fetches new Zendesk tickets, drafts a reply from Notion knowledge base articles, digests what it cannot answer to Slack, and archives the rest, acting as the support agent rather than a shared API key.

Support and Ops Teams

Meeting prep

Pulls agenda, participant context, and open action items before every meeting.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

01.

Shared tokens break per-user analytics

A shared Ragie access token looks fine in a demo. In production every document change looks like one service account, and you cannot tell which user triggered it. Scalekit resolves the credential of the actual user who triggered the agent, never a shared bot.

// shared key
audit → bot_service_account

// scalekit
audit → user_abc ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

Ragie today. Ten connectors tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access Ragie as the user or through a shared access token?

As the user. Each user connects their own Ragie access token once, and Scalekit sends it with every call. Audit logs attribute every document ingest and change to that user, not a shared service account.

Where is the Ragie access token stored?

In Scalekit's managed AES-256 token vault, namespaced per tenant. To rotate it, the user reconnects with a new access token. Revocation is a single dashboard action. Credentials never appear in prompts, logs, or LLM context.

Can I limit what the agent does in Ragie?

Yes. Filter by tool name in listScopedTools to expose only what you want, for example retrieval and document reads without ragie_document_delete or ragie_partition_delete, which deletes a partition and every document inside it. Scalekit also enforces scope checks before every API call.

What happens when a user revokes Ragie access?

The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Can the agent keep separate customers' documents apart?

Yes, with partitions. ragie_partition_create isolates a set of documents with optional usage limits, and ragie_retrieve searches only the partition you pass, or the default partition when you pass none.