PostHog MCP

CALL ANY TOOL

Query events with HogQL, list insights and dashboards, check feature flag rollout, browse persons and cohorts.

posthog_events_query

Query events

Run a HogQL or filter-based query against PostHog event data.

Parameters

Name

Type

Required

Description

query

string

Required

HogQL query or event filter JSON

date_from

string

Optional

Start date: YYYY-MM-DD or relative like -7d

date_to

string

Optional

End date

limit

integer

Optional

Max rows

posthog_insights_list

List insights

posthog_feature_flags_list

List feature flags

posthog_persons_list

List persons

posthog_cohorts_list

List cohorts

Build your Agent

Drop the toolkit in, point it at the user, and your product analytics agent can use PostHog MCP 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: ["posthogmcp"], toolNames: ["posthog_events_query", "posthog_insights_list", "posthog_feature_flags_list"] },
  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: ["posthogmcp"], toolNames: ["posthog_events_query", "posthog_insights_list", "posthog_feature_flags_list"] },
  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: ["posthogmcp"], toolNames: ["posthog_events_query", "posthog_insights_list", "posthog_feature_flags_list"] },
  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 }],
});

Copied

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/posthogmcp",
    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 PostHog MCP.

Events & funnels

Copy the prompt

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Activation funnel for signups this week.

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Daily active users for the last 30 days.

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Top 10 events by volume today.

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Query: SELECT event, count() FROM events WHERE timestamp > now() - interval 7 day GROUP BY event.

Feature flags & cohorts

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List all active feature flags.

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Which flags have rollout below 20%?

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List all cohorts and their sizes.

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Which users are in cohort [name]?

Insights & reporting

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List all saved insights.

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Which insight tracks [metric]?

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Retention curve for users who signed up last month.

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Session recording count by page this week.

SEE HOW AUTH WORKS

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

1

Authorize

Your user connects

PostHog 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

PostHog 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

PostHog 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

PostHog 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

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

ENGINEERING

Engineering standup agent

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

ENGINEERING

DevOps assistant agent

Triage GitHub incidents, open Linear tickets, and notify the on-call channel in Slack with context already attached.

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.

PostHog MCP 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 PostHog MCP 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 PostHog MCP api key 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 PostHog MCP?

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

What happens when a user revokes PostHog MCP 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.

Does the agent inherit my PostHog project and org access?

Yes. The API key is scoped to the project it was created in. The agent can only access data within that project. Cross-project queries require a separate connected account per project.

Tools your product analytics agent reaches for on PostHog MCP, scoped per user.