Microsoft Word MCP | OAuth 2.0 Microsoft Word connector for AI agents

CALL ANY TOOL

List and read Word documents, extract text content, create new files, and share with collaborators.

word_documents_list

List documents

List Word documents in the user's OneDrive or SharePoint.

Parameters

Name

Type

Required

Description

limit

integer

Optional

Max documents

query

string

Optional

Search query

word_document_get

Get document

word_document_content

Read content

word_document_create

Create document

word_document_share

Share document

Build your Agent

Drop the toolkit in, point it at the user, and your document agent can use Microsoft Word from the first run.

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import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { z } from "zod";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["microsoftword"], toolNames: ["word_documents_list", "word_document_get", "word_document_content"] },
  pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  schema: z.object({}).passthrough(),
  func: async (args) => {
    const { data } = await sk.tools.executeTool({
      toolName: t.tool.definition.name,
      identifier: "user_123",
      params: args,
    });
    return JSON.stringify(data);
  },
}));

const agent = createReactAgent({ llm, tools: lcTools });

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

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["microsoftword"], toolNames: ["word_documents_list", "word_document_get", "word_document_content"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  type: "function",
  function: {
    name: t.tool.definition.name,
    description: t.tool.definition.description,
    parameters: t.tool.definition.input_schema,
  },
}));

const resp = await openai.responses.create({
  model: "gpt-4o", input: prompt, tools: llmTools,
});

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

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["microsoftword"], toolNames: ["word_documents_list", "word_document_get", "word_document_content"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
  model: "claude-sonnet-4-6", max_tokens: 1024,
  tools: llmTools,
  messages: [{ role: "user", content: prompt }],
});

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import { Agent } from "@google/adk/agents";
import {
  MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
  connectionParams: new StreamableHTTPConnectionParams({
    url: "https://mcp.scalekit.com/microsoftword",
    headers: { Authorization: `Bearer ${userScopedToken}` },
  }),
});

const agent = new Agent({
  name: "agent", model: "gemini-2.0-flash",
  tools: await toolset.getTools(),
});

Try these prompts

Paste any prompt into your agent to start using Microsoft Word.

Search & recall

Copy the prompt

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Find all Word docs with [keyword] in the title.

Copy the prompt

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Get content of [document name].

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List documents updated this week.

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Find contracts shared with [email].

Action & creation

Copy the prompt

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Create a new document titled [title].

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Read the full text of [document name].

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Share [document] with [email] as editor.

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Find all documents in [folder].

Reporting

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Which documents were created this month?

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List docs owned by [email].

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Find documents larger than 5MB.

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Which docs haven't been updated in 90 days?

SEE HOW AUTH WORKS

Users authorize Microsoft Word once. Their credentials stay vaulted, every call is checked, and every action is logged.

1

Authorize

Your user connects

Microsoft Word

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

2

Store

Their

Microsoft Word

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

3

Resolve

When your agent calls a

Microsoft Word

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

4

Audit

Every

Microsoft Word

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

Same per-user auth pattern across other document agents and MCP connectors. Working code, live demos, fork what fits.

SUPPORT

Support ticket automation (Google ADK)

Google ADK agent that classifies Zendesk tickets, pulls Notion context, and posts to Slack. End-to-end ticket handoff.

ENGINEERING

Engineering standup agent

Aggregate GitHub and GitLab activity, link to Jira, and post a daily standup digest to Slack. No async updates.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

Other connector libraries treat auth as a demo afterthought. Scalekit starts with user identity, scope enforcement, and audit.

01.

Shared tokens break per-user analytics

A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential so attribution, audit, and scope stay accurate.

// shared token
 audit → bot_service_account
 user_filter → broken

 // scalekit
 audit → user_abc
 scope → enforced ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

Microsoft Word today. Others 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 Microsoft Word as the user or as a shared key?

As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the Microsoft Word oauth 2.0 stored?

In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in Microsoft Word?

Yes. Pass a tool name filter to listScopedTools so the document agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Microsoft Word.

What happens when a user revokes Microsoft Word 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 read documents stored in SharePoint sites the user is not a member of?

No. Document access resolves the authorizing user's Microsoft OAuth permissions. SharePoint sites and document libraries the user hasn't been granted access to are inaccessible.

Microsoft Word

Tools your document agent reaches for on Microsoft Word, scoped per user.