Mixpanel Analytics connector for AI agents

Tools your analytics agent reaches for on Mixpanel Analytics, scoped per tenant.

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Product analytics across the Query API, Lexicon schemas, and warehouse connectors: segmentation, funnels, retention, Insights, profiles, and custom JQL.

mixpanelanalytics_cohorts_list

List cohorts

List every saved cohort in a mixpanel project, including each cohort's numeric id, name, member count, description, and creation date. use the id with 'mixpanelanalytics_profiles_query' (filter_by_cohort) to fetch the profiles in a cohort.

Parameters

Name

Type

Required

Description

project_id

integer

Required

Your Mixpanel numeric Project ID (Project Settings > Overview). Required when authenticating with a Service Account; not needed with a legacy Project Secret.

workspace_id

integer

Optional

The numeric ID of the Mixpanel workspace to query, for projects with multiple workspaces. Omit to use the project's default workspace.

mixpanelanalytics_schema_get

Get schema

mixpanelanalytics_events_query

Query events

mixpanelanalytics_warehouse_import_create_event_stream

Warehouse import create event stream

Create a new warehouse import that streams warehouse rows into mixpanel as events. maps a warehouse table to mixpanel's events dataset using 'table_params' to select the source table/columns and 'time_column_name' (plus 'event_name' or 'event_column_name') to derive each event's timestamp and name. requires a warehouse source to already be configured in mixpanel (lexicon > warehouse sources): pass its id as 'warehouse_source_id'. requires warehouse connectors to be enabled on your mixpanel plan; without it, calls to this endpoint return a 403 forbidden regardless of input.

Parameters

Name

Type

Required

Description

project_id

string

Required

Your numeric Mixpanel Project ID, required to authenticate Service Account requests. Find it in Mixpanel under Project Settings > Overview.

sync_mode

string

Required

How this import stays in sync with the warehouse table over time, e.g. a full re-sync mode or an incremental mode based on a time column. Mixpanel's Warehouse Connectors API does not fully document every valid value for this import type in one place: the sibling lookup-table import accepts 'full_sync' or 'one_time', but event/people/group streaming imports may support additional incremental modes. Check your warehouse source configuration in the Mixpanel dashboard, or current Mixpanel documentation, to confirm the exact values accepted before relying on a value here.

table_params

object

Required

JSON object describing which warehouse table (and columns) this import reads from, e.g. the database, schema, and table name. The exact shape depends on your warehouse type (Snowflake, BigQuery, Databricks, or Redshift) and is passed through to Mixpanel as-is: check an existing import's configuration (via 'mixpanelanalytics_warehouse_import_get') or current Mixpanel documentation for the precise fields your warehouse type expects. Example: {"schema": "public", "table_name": "events"}.

time_column_name

string

Required

The name of the warehouse column containing each row's event timestamp. Mixpanel uses this column to set the imported event's time.

warehouse_source_id

integer

Required

The numeric ID of the warehouse source (the connected Snowflake, BigQuery, Databricks, or Redshift warehouse) this import reads from. Warehouse sources are configured separately in Mixpanel under Lexicon > Warehouse Sources.

company_column_name

string

Optional

The name of the warehouse column containing a company/account identifier to associate with each imported event, for B2B group analytics.

databricks_params

object

Optional

Databricks-specific cluster configuration for this import, passed through to Mixpanel as-is. Only relevant when the underlying warehouse source is Databricks: omit for Snowflake, BigQuery, or Redshift sources. Check current Mixpanel documentation or an existing Databricks import (via 'mixpanelanalytics_warehouse_import_get') for the exact fields expected, such as a cluster id or SQL warehouse id.

device_column_name

string

Optional

The name of the warehouse column containing a device identifier to associate with each imported event.

event_column_name

string

Optional

The name of the warehouse column whose value supplies each row's event name, when different rows should become different event types. Provide this or a fixed 'event_name'.

event_name

string

Optional

A fixed event name to apply to every row imported from this table. Provide this or 'event_column_name' (a column whose value supplies the event name per-row): check Mixpanel's current Warehouse Connectors documentation for which one your use case requires.

insert_time_column_name

string

Optional

The name of a warehouse column marking when each row was inserted into the warehouse, used by Mixpanel to incrementally pick up only new rows on subsequent syncs instead of rescanning the whole table.

json_properties_column_name

string

Optional

The name of a warehouse column containing a JSON blob of additional event properties to merge into each imported event, for schemas that store extra attributes as a single JSON column rather than one column per property.

property_mappings

object

Optional

JSON object remapping warehouse column names to different Mixpanel property names on import, e.g. {"warehouse_col": "Mixpanel Property Name"}. Omit to import columns using their original warehouse column names.

run_every

integer

Optional

How often this warehouse import syncs, in NANOSECONDS: not seconds or milliseconds. This unit is easy to get wrong: 86400000000000 nanoseconds = 1 day (86400 seconds × 1,000,000,000). Common values: 3600000000000 = hourly, 86400000000000 = daily, 604800000000000 = weekly. Omit to keep Mixpanel's default sync frequency for this import type.

user_column_name

string

Optional

The name of the warehouse column containing the user identifier (Mixpanel distinct_id) to associate with each imported event.

mixpanelanalytics_warehouse_import_update

Update warehouse import

mixpanelanalytics_schema_delete

Delete schema

mixpanelanalytics_funnels_list_saved

Funnels list saved

mixpanelanalytics_warehouse_import_get

Get warehouse import

mixpanelanalytics_funnels_query

Query funnels

mixpanelanalytics_warehouse_import_create_groups

Warehouse import create groups

Create a new warehouse import that syncs warehouse rows into mixpanel as group profile updates, analogous to 'mixpanelanalytics_warehouse_import_create_people' but for group analytics (e.g. company/account-level profiles) instead of individual users. maps a warehouse table using 'table_params', with 'group_key' naming the configured mixpanel group type and 'group_id_column' identifying which warehouse column holds each row's group id. requires a warehouse source to already be configured in mixpanel (lexicon > warehouse sources): pass its id as 'warehouse_source_id'. requires group analytics to be enabled on your mixpanel project, and warehouse connectors to be enabled on your mixpanel plan; without the latter, calls to this endpoint return a 403 forbidden regardless of input.

Parameters

Name

Type

Required

Description

group_id_column

string

Required

The name of the warehouse column containing each row's group identifier (the value for the group key above), e.g. the company name or account ID column.

group_key

string

Required

The name of the group key as configured in Mixpanel for this group analytics type, e.g. "Company" or "Account ID". This must match a group key already defined in your project.

project_id

string

Required

Your numeric Mixpanel Project ID, required to authenticate Service Account requests. Find it in Mixpanel under Project Settings > Overview.

sync_mode

string

Required

table_params

object

Required

warehouse_source_id

integer

Required

databricks_params

object

Optional

insert_time_column_name

string

Optional

json_properties_column_name

string

Optional

The name of a warehouse column containing a JSON blob of additional group properties to merge into each imported group profile, for schemas that store extra attributes as a single JSON column rather than one column per property.

property_mappings

object

Optional

run_every

integer

Optional

mixpanelanalytics_schemas_delete_all

Schemas delete all

mixpanelanalytics_schemas_list

List schemas

mixpanelanalytics_insights_query

Query insights

mixpanelanalytics_warehouse_import_create_lookup_table

Warehouse import create lookup table

Create a new warehouse import that syncs a warehouse table into mixpanel as a lookup table, joining additional properties onto events or user profiles by a shared key (similar in effect to 'mixpanelingestion_lookup_table_replace', but kept continuously in sync from the warehouse instead of being replaced manually via csv). 'mixpanel_property' identifies which mixpanel property this table enriches, and 'property_key_column_name' is the warehouse column holding the join key. requires a warehouse source to already be configured in mixpanel (lexicon > warehouse sources): pass its id as 'warehouse_source_id'. requires warehouse connectors to be enabled on your mixpanel plan; without it, calls to this endpoint return a 403 forbidden regardless of input.

Parameters

Name

Type

Required

Description

mixpanel_property

object

Required

JSON object identifying which Mixpanel property this lookup table enriches. Shape: {"value": , "resourceType": , "customPropertyId": }. Example: {"value": "Total Revenue", "resourceType": "event", "customPropertyId": null} enriches the event property "Total Revenue". Find the exact property identifiers in Lexicon.

project_id

string

Required

Your numeric Mixpanel Project ID, required to authenticate Service Account requests. Find it in Mixpanel under Project Settings > Overview.

property_key_column_name

string

Required

The name of the warehouse column containing the lookup key: the value that matches this property's values on incoming events or profiles.

sync_mode

string

Required

How this lookup table import stays in sync with the warehouse table. 'full_sync' re-imports the entire table on every scheduled run (see 'run_every'), keeping it continuously up to date. 'one_time' imports the table once and does not sync again automatically.

table_params

object

Required

warehouse_source_id

integer

Required

databricks_params

object

Optional

run_every

integer

Optional

mixpanelanalytics_schemas_delete_by_entity

Schemas delete by entity

mixpanelanalytics_schemas_list_by_entity

Schemas list by entity

mixpanelanalytics_jql_query

Query jql

mixpanelanalytics_warehouse_import_create_people

Warehouse import create people

Create a new warehouse import that syncs warehouse rows into mixpanel as user profile updates (equivalent to engage '$set'). maps a warehouse table to mixpanel user profiles using 'table_params' to select the source table/columns and 'user_column_name' to identify which column holds each profile's distinct_id. requires a warehouse source to already be configured in mixpanel (lexicon > warehouse sources): pass its id as 'warehouse_source_id'. requires warehouse connectors to be enabled on your mixpanel plan; without it, calls to this endpoint return a 403 forbidden regardless of input.

Parameters

Name

Type

Required

Description

project_id

string

Required

Your numeric Mixpanel Project ID, required to authenticate Service Account requests. Find it in Mixpanel under Project Settings > Overview.

sync_mode

string

Required

table_params

object

Required

user_column_name

string

Required

The name of the warehouse column containing the user identifier (Mixpanel distinct_id) that each row's profile updates apply to.

warehouse_source_id

integer

Required

databricks_params

object

Optional

insert_time_column_name

string

Optional

json_properties_column_name

string

Optional

The name of a warehouse column containing a JSON blob of additional profile properties to merge into each imported profile, for schemas that store extra attributes as a single JSON column rather than one column per property.

property_mappings

object

Optional

run_every

integer

Optional

mixpanelanalytics_warehouse_import_delete

Delete warehouse import

mixpanelanalytics_warehouse_imports_list

List warehouse imports

mixpanelanalytics_profiles_query

Query profiles

mixpanelanalytics_retention_frequency_query

Query retention frequency

mixpanelanalytics_retention_query

Query retention

mixpanelanalytics_segmentation_average_query

Query segmentation average

mixpanelanalytics_segmentation_numeric_query

Query segmentation numeric

mixpanelanalytics_segmentation_query

Query segmentation

mixpanelanalytics_segmentation_sum_query

Query segmentation sum

mixpanelanalytics_activity_stream

Activity stream

mixpanelanalytics_event_properties

Event properties

mixpanelanalytics_events_top_names

Events top names

For more tools, view docs.

Build your Agent

Drop the toolkit in, point it at the tenant, and your agent can run funnel and retention queries from the first run.

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: ["mixpanelanalytics"], toolNames: ["mixpanelanalytics_events_query", "mixpanelanalytics_funnels_query", "mixpanelanalytics_retention_query"] },
  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 });

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: ["mixpanelanalytics"], toolNames: ["mixpanelanalytics_events_query", "mixpanelanalytics_funnels_query", "mixpanelanalytics_retention_query"] },
  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: ["mixpanelanalytics"], toolNames: ["mixpanelanalytics_events_query", "mixpanelanalytics_funnels_query", "mixpanelanalytics_retention_query"] },
  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 }],
});

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/mixpanelanalytics",
    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 querying Mixpanel from your workflows.

Funnels and retention

Copy the prompt

Copied

Show conversion for saved funnel [funnel_id] over the last 14 days.

Copy the prompt

Copied

Compare week-one retention for users who did [event] against those who did not.

Copy the prompt

Copied

Which step in [funnel_id] lost the most users this month?

Event exploration

Copy the prompt

Copied

List the top events today with percent change against yesterday.

Copy the prompt

Copied

Break [event] down by the values of [property] for last week.

Copy the prompt

Copied

Show the activity stream for distinct_id [id] over the last 7 days.

Schemas and profiles

Copy the prompt

Copied

List event properties with no Lexicon description.

Copy the prompt

Copied

Query profiles where plan is enterprise and last_seen is over 30 days ago.

Copy the prompt

Copied

Run this JQL script and summarize the output.

SEE HOW AUTH WORKS

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

Authorize

Your user connects

Mixpanel Analytics

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

Mixpanel Analytics

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

Mixpanel Analytics

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

Mixpanel Analytics

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 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.

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.

Mixpanel Analytics 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 Mixpanel Analytics 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 Mixpanel Analytics service account 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 Mixpanel Analytics?

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

What happens when a user revokes Mixpanel Analytics 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 a query in one tenant read another tenant's Mixpanel project?

No. The service account you register is project scoped and lives in that tenant's namespace of the AES-256 vault. Scalekit resolves it per request, so a query issued for one tenant can only touch that tenant's project.

On this page

Tool and actions Framework Compatibility Starter Prompt Auth Lifecycle Try Other Agents Why Scalekit