Mixpanel Ingestion MCP server for AI agents

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SERVICE ACCOUNT

EVENT INGESTION

Analytics

Event ingestion, profile updates, identity merges, and lookup tables all run through Mixpanel's Ingestion API, reached with a service account Scalekit vaults per tenant.

  • One vaulted service account: ingestion credentials resolve at request time for the right project, never in a prompt or a log line.
  • Credentials stay vaulted: AES-256, resolved at request time, never in LLM context.
  • Scoped before every call: User permissions enforced. 90-day audit trail.
Mixpanel Ingestion
agent · Acme Q3
Run
Backfill yesterday's signup events and set the plan property on those profiles.
S
mixpanelingestion_import_events
212ms
Data agent
Imported 1,428 signup events for Nov 27 and set plan on 1,428 profiles. 0 rejected, 3 deduped against existing insert_ids.
Sources: 1,428 events, 1,428 profiles
mixpanelingestion
2 calls
18:29
Message Claude...

Tools your data agent reaches for on Mixpanel Ingestion, scoped per tenant.

CALL ANY TOOL
Event ingestion and profile management in one toolkit: import events, set and union profile properties, group profiles, identity merges, lookup tables, and flag evaluation.
mixpanelingestion_feature_flags_definitions
Feature flags definitions
Get the full definitions of every feature flag/experiment configured in a Mixpanel project, including each flag's variants, rollout rules, and linked experiment. Provide either 'project_token' or 'project_id' to authenticate (project_id uses your Service Account credentials).
Parameters
Name
Type
Required
Description
project_id
string
Optional
Your numeric Mixpanel Project ID, used if authenticating with a Service Account. Provide this or 'project_token'.
project_token
string
Optional
Your Mixpanel Project Token, used if authenticating without a Service Account. Provide this or 'project_id'.
mixpanelingestion_feature_flags_evaluate
Feature flags evaluate
mixpanelingestion_group_batch_update
Update group batch
mixpanelingestion_group_delete
Delete group
mixpanelingestion_group_remove
Remove group
mixpanelingestion_group_set
Set group
mixpanelingestion_group_set_once
Group set once
mixpanelingestion_group_union
Group union
mixpanelingestion_group_unset
Group unset
mixpanelingestion_identity_create
Create identity
mixpanelingestion_identity_create_alias
Identity create alias
mixpanelingestion_identity_merge
Merge identity
mixpanelingestion_import_events
Import events
mixpanelingestion_lookup_table_replace
Lookup table replace
mixpanelingestion_lookup_tables_list
List lookup tables
mixpanelingestion_profile_append
Profile append
mixpanelingestion_profile_batch_update
Update profile batch
mixpanelingestion_profile_delete
Delete profile
mixpanelingestion_profile_increment
Profile increment
mixpanelingestion_profile_remove
Remove profile
mixpanelingestion_profile_set
Set profile
mixpanelingestion_profile_set_once
Profile set once
mixpanelingestion_profile_union
Profile union
mixpanelingestion_profile_unset
Profile unset
mixpanelingestion_track_event
Track event
Build your Agent
Drop the toolkit in, point it at the tenant, and your agent can import events and update profiles from the first run.
Python · LlamaIndex
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: ["mixpanelingestion"], toolNames: ["mixpanelingestion_import_events", "mixpanelingestion_profile_set", "mixpanelingestion_identity_merge"] },
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: ["mixpanelingestion"], toolNames: ["mixpanelingestion_import_events", "mixpanelingestion_profile_set", "mixpanelingestion_identity_merge"] },
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: ["mixpanelingestion"], toolNames: ["mixpanelingestion_import_events", "mixpanelingestion_profile_set", "mixpanelingestion_identity_merge"] },
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/mixpanelingestion",
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 running Mixpanel ingestion from your workflows.
Event import
Copy the prompt
Copied
Import these events for [date] and report anything rejected.
Copy the prompt
Copied
Backfill signup events for last week and dedupe on insert_id.
Copy the prompt
Copied
Track a single [event] for distinct_id [id] with these properties.
Profiles and groups
Copy the prompt
Copied
Set plan and mrr on profile [distinct_id].
Copy the prompt
Copied
Union the feature_flags property on these profiles instead of overwriting.
Copy the prompt
Copied
Batch update group profiles for org [group_id].
Identity and lookups
Copy the prompt
Copied
Merge distinct_id [a] into [b] and confirm the surviving id.
Copy the prompt
Copied
Replace the lookup table for plan tiers with this CSV.
Copy the prompt
Copied
Evaluate feature flags for distinct_id [id].
SEE HOW AUTH WORKS
You connect a service account once. Your Mixpanel Ingestion credentials stay vaulted, every call is scope-checked, and every action is logged.
1
Authorize
Your user connects
Mixpanel Ingestion
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
Mixpanel Ingestion
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
Mixpanel Ingestion
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
Mixpanel Ingestion
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 auth, scope, and audit pattern across other 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 auth, scope, and audit 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.
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 token looks fine in a demo. In production you need to know which agent and tenant made each call. Scalekit resolves the tenant's vaulted service account 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 Ingestion 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
How does the agent authenticate to Mixpanel Ingestion?
You connect Mixpanel Ingestion once with a service account, and Scalekit authenticates every call. Audit logs record every action the agent takes.
Where are the Mixpanel Ingestion service account credentials stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Revocation is a single dashboard action. Credentials never appear in prompts, logs, or LLM context.
Can I limit what the agent is allowed to do in Mixpanel Ingestion?
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 Ingestion.
What happens when the Mixpanel Ingestion service account is revoked?
The connection is invalidated on the next tool call. Subsequent requests for that tenant fail closed with a clear error. Other tenants remain unaffected. The event is logged for audit.
What stops an agent from writing junk events into production?
Scope and separation. Ingestion tools are separate from the delete and lookup-replace tools, so you expose only what a given agent needs. Every call is scope-checked before it reaches Mixpanel, attributed to the calling agent and tenant, and kept in the 90-day audit chain for replay.
Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""mixpanelingestion"": {
""url"": ""https://mcp.scalekit.com/mixpanelingestion"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.mixpanelingestion]
url = ""https://mcp.scalekit.com/mixpanelingestion""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""mixpanelingestion"": {
""url"": ""https://mcp.scalekit.com/mixpanelingestion"",
""type"": ""http""
}
}
}