Catchr MCP connector for AI agents

CALL ANY TOOL

Marketing data end to end: list connected platforms and accounts, explore the field catalog, and run metric queries across ad sources.

catchrmcp_list_sources

List sources

List network authorizations (sources) for the authenticated company, with optional available accounts.

Parameters

Name

Type

Required

Description

includeAvailableAccounts

boolean

Optional

When true, include the list of available accounts for each source.

platform

string

Optional

Filter sources to a specific platform identifier.

catchrmcp_run_api_request_json

Run api request json

catchrmcp_list_platforms

List platforms

catchrmcp_describe_run_api_request_schema

Describe run api request schema

catchrmcp_list_all_fields

List all fields

catchrmcp_list_available_accounts

List available accounts

catchrmcp_list_fields_by_platform

List fields by platform

catchrmcp_list_fields_for_account

List fields for account

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);

// Catchr tools scoped to this user
const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["catchrmcp"], toolNames: [
    "catchrmcp_list_available_accounts",
    "catchrmcp_list_fields_by_platform",
    "catchrmcp_run_api_request_json"] },
  pageSize: 100,
});

const agent = createReactAgent({ llm, tools });
await agent.invoke({ messages: [{ role: "user", content: "How did Google Ads spend trend last week?" }] });

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: ["catchrmcp"] }, pageSize: 100,
});

const res = await openai.chat.completions.create({
  model: "gpt-5",
  messages: [{ role: "user", content: "Which ad platforms are connected for this company?" }],
  tools,
});

// Execute the tool call with the user's vaulted Catchr credential
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: ["catchrmcp"] }, pageSize: 100,
});

const msg = await anthropic.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Compare CPC across Google Ads and Facebook Ads this month." }],
  tools,
});

// Tool call runs with the user's vaulted Catchr credential
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: ["catchrmcp"] }, pageSize: 100,
});

const agent = new Agent({
  name: "catchr_reporting_agent",
  model: "gemini-2.5-pro",
  instruction: "Answer marketing data questions for the signed-in user.",
  tools,
});

await agent.run("Which campaigns had the highest ROAS last month?");

Try these prompts

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

Ad performance

Copy the prompt

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How did Google Ads spend trend last week versus the week before?

Copy the prompt

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Which campaigns had the highest ROAS last month?

Copy the prompt

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Pull impressions, clicks, and CPC for the top 10 Facebook ad sets.

Explore sources and fields

Copy the prompt

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Which ad platforms are connected for this company?

Copy the prompt

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List the ad accounts available under our Google Ads authorization.

Copy the prompt

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What conversion fields does Catchr expose for Facebook Ads?

Cross-platform reporting

Copy the prompt

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Compare CPC across Google Ads and Facebook Ads this month.

Copy the prompt

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Build a weekly spend summary across every connected account.

Copy the prompt

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Total conversions by platform for Q2, sorted highest first.

SEE HOW AUTH WORKS

Your users connect once. Their Catchr credentials stay vaulted, every call is scope-checked, and every action is logged.

1

Authorize

Your user connects

Catchr MCP

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

Catchr MCP

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

Catchr MCP

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

Catchr MCP

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 analytics connectors.

GTM and RevOps Teams

Revenue forecast commentary

Pulls open pipeline from Salesforce and HubSpot, calculates coverage against quota, flags at-risk stages, posts commentary to Slack, and logs every snapshot to Google Sheets.

GTM and RevOps Teams

Deal intelligence agent

Pulls recent Gong calls, scores deal risk with an LLM, cross-references the record in Attio, and DMs each owner their at-risk deals in Slack. Every read is scoped to that rep's own access.

Engineering Teams

Engineering standup agent

Pulls commits from GitHub and GitLab, tracks issue movement in Jira, and posts a per-engineer standup brief to Slack. Each engineer's activity is read on their own delegated OAuth.

GTM and RevOps Teams

Competitive intelligence briefing agent

Scans Gong calls for competitor mentions, matches each one to its Notion battlecard, and DMs every affected rep a single Slack digest per cycle. Every call runs as the PMM who owns the briefing, never a shared bot.

Test other agents

See the same per-user auth pattern across other analytics connectors.

SALES

Deal intelligence agent

Score Gong call risk with an LLM, cross-reference the Attio record, and DM each owner their at-risk deals in Slack.

ENGINEERING

Engineering standup agent

Pull commits from GitHub and GitLab, track Jira issue movement, and post a per-engineer standup brief to Slack.

GTM

Revenue forecast agent

Score pipeline coverage against quota across Salesforce and HubSpot, post forecast commentary to Slack, log snapshots to Sheets.

GTM

Competitive intelligence briefing agent

Scan Gong calls for competitor mentions, match each one to its Notion battlecard, and DM every affected rep a single Slack digest.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

01.

Shared tokens break per-user analytics

A shared Catchr key looks fine in a demo. In production every metric query across every client's ad accounts looks like one service account, and you cannot tell who pulled which numbers. 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.

Catchr 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 Catchr as the user or through a shared key?

As the user. Scalekit resolves the credential of the person who triggered the agent at request time, so every metric query in your audit trail is attributed to a real user, not a shared service account.

Where is the Catchr API key stored?

In an AES-256 encrypted vault with per-tenant namespacing. Keys are resolved at request time, never enter LLM context, and can be rotated or revoked from one dashboard.

Can I limit what the agent does in Catchr?

Yes. Filter by tool name in listScopedTools to expose only what you want, for example field discovery without run_api_request_json. Scalekit also enforces scope checks before every API call.

What happens when a user revokes access?

The credential is invalidated at the next tool call. The call fails closed, other users' connections are unaffected, and the revocation is logged in the audit chain.

Which ad accounts can the agent actually query?

Only the accounts under the network authorizations your company connected in Catchr. The agent discovers them with list_sources and list_available_accounts, and every run_api_request_json call is scoped to those accounts and logged with the requesting user.

Catchr MCP

Tools your reporting agent reaches for on Catchr, scoped per user.