Vibecode Mixpanel
track this build5 steps, step by step0%A consolation build is possible, but the paid product's decisive value sits outside a solo rebuild. For Mixpanel, collect a small transparent event stream and build funnels and retention locally. The hard boundary is large-scale ingestion, identity handling, query engine, governance, and product expertise, plus data pipeline reliability and analytical depth.
You are building a lean indie version of Mixpanel. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Mixpanel indie build ## Goal Build the smallest trustworthy replacement for the core Mixpanel workflow for one developer or a tiny team. ## Scope Collect a small transparent stream of privacy-conscious first-party events, build funnels and retention views locally, answer a small set of product questions, and retain raw data under the owner's control. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - large-scale ingestion, identity handling, query engine, governance, and product expertise - identity stitching - session replay - warehouse connectors - high-volume global ingestion and support If those capabilities are essential, use Umami instead of pretending the gap is solved. ===== AGENTS.md ===== # Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs". ===== BUILD_PLAN.md ===== # Build plan ## Original build brief Build a closest honest personal substitute for Mixpanel in an empty repository. Use Next.js 15, TypeScript, ClickHouse, PostgreSQL, and Docker Compose; do not offer alternative stacks. The core loop is: collect a small transparent stream of privacy-conscious first-party events, build funnels and retention views locally, answer a small set of product questions, and retain raw data under the owner's control. Make the first run work locally with one documented command. Store all user data locally by default and make export straightforward. Put secrets in .env, ship .env.example, and never commit credentials. Ship a lightweight browser SDK for page views and explicit custom events. Create projects, API keys, environments, event names, and a documented event schema. Ingest idempotently, filter obvious bots, truncate IP data, and avoid fingerprinting. Build dashboards for visitors, sessions, funnels, retention, sources, pages, and events. Expose filters by date, environment, device, country, referrer, and selected properties. Add retention controls, raw-event export, deletion, health checks, and backup instructions. Include clear empty, loading, success, and recoverable error states. Add input validation, safe filenames, and graceful handling of unavailable APIs. Write focused tests for the core transformation and one end-to-end happy path. Create a README with setup, architecture, permissions, data location, and backup steps. Do not add accounts, billing, telemetry, analytics, or a hosted control plane. Do not claim to reproduce proprietary data, network liquidity, regulated access, or frontier infrastructure. Deliberately leave out cross-site identity graphs. Deliberately leave out session replay and automatic DOM capture. Deliberately leave out warehouse-scale reverse ETL and enterprise governance. Finish by running the tests and listing the exact commands used. ## Required capabilities - Docker - ClickHouse - PostgreSQL - public HTTPS collector endpoint - site script access ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden. ===== .env.example ===== # Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
You are building a lean indie version of Mixpanel. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== README.md ===== # Mixpanel indie build ## Goal Build the smallest trustworthy replacement for the core Mixpanel workflow for one developer or a tiny team. ## Scope Collect a small transparent stream of privacy-conscious first-party events, build funnels and retention views locally, answer a small set of product questions, and retain raw data under the owner's control. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - large-scale ingestion, identity handling, query engine, governance, and product expertise - identity stitching - session replay - warehouse connectors - high-volume global ingestion and support If those capabilities are essential, use Umami instead of pretending the gap is solved. ===== AGENTS.md ===== # Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs". ===== BUILD_PLAN.md ===== # Build plan ## Original build brief Build a closest honest personal substitute for Mixpanel in an empty repository. Use Next.js 15, TypeScript, ClickHouse, PostgreSQL, and Docker Compose; do not offer alternative stacks. The core loop is: collect a small transparent stream of privacy-conscious first-party events, build funnels and retention views locally, answer a small set of product questions, and retain raw data under the owner's control. Make the first run work locally with one documented command. Store all user data locally by default and make export straightforward. Put secrets in .env, ship .env.example, and never commit credentials. Ship a lightweight browser SDK for page views and explicit custom events. Create projects, API keys, environments, event names, and a documented event schema. Ingest idempotently, filter obvious bots, truncate IP data, and avoid fingerprinting. Build dashboards for visitors, sessions, funnels, retention, sources, pages, and events. Expose filters by date, environment, device, country, referrer, and selected properties. Add retention controls, raw-event export, deletion, health checks, and backup instructions. Include clear empty, loading, success, and recoverable error states. Add input validation, safe filenames, and graceful handling of unavailable APIs. Write focused tests for the core transformation and one end-to-end happy path. Create a README with setup, architecture, permissions, data location, and backup steps. Do not add accounts, billing, telemetry, analytics, or a hosted control plane. Do not claim to reproduce proprietary data, network liquidity, regulated access, or frontier infrastructure. Deliberately leave out cross-site identity graphs. Deliberately leave out session replay and automatic DOM capture. Deliberately leave out warehouse-scale reverse ETL and enterprise governance. Finish by running the tests and listing the exact commands used. ## Required capabilities - Docker - ClickHouse - PostgreSQL - public HTTPS collector endpoint - site script access ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden. ===== .env.example ===== # Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
You are building a production product version of Mixpanel. Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt. ===== PRODUCT.md ===== # Mixpanel product brief ## Problem A consolation build is possible, but the paid product's decisive value sits outside a solo rebuild. For Mixpanel, collect a small transparent event stream and build funnels and retention locally. The hard boundary is large-scale ingestion, identity handling, query engine, governance, and product expertise, plus data pipeline reliability and analytical depth. ## Product outcome Collect a small transparent stream of privacy-conscious first-party events, build funnels and retention views locally, answer a small set of product questions, and retain raw data under the owner's control. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - Docker - ClickHouse - PostgreSQL - public HTTPS collector endpoint - site script access ## Explicit non-goals for v1 - large-scale ingestion, identity handling, query engine, governance, and product expertise - identity stitching - session replay - warehouse connectors - high-volume global ingestion and support ## Success criteria - The primary workflow is measurable end to end. - Setup is reproducible in a clean environment. - Failure, recovery, and support paths are documented. - Product claims match what the implementation actually guarantees. ===== ARCHITECTURE.md ===== # Architecture ## Starting brief Build a closest honest personal substitute for Mixpanel in an empty repository. Use Next.js 15, TypeScript, ClickHouse, PostgreSQL, and Docker Compose; do not offer alternative stacks. The core loop is: collect a small transparent stream of privacy-conscious first-party events, build funnels and retention views locally, answer a small set of product questions, and retain raw data under the owner's control. Make the first run work locally with one documented command. Store all user data locally by default and make export straightforward. Put secrets in .env, ship .env.example, and never commit credentials. Ship a lightweight browser SDK for page views and explicit custom events. Create projects, API keys, environments, event names, and a documented event schema. Ingest idempotently, filter obvious bots, truncate IP data, and avoid fingerprinting. Build dashboards for visitors, sessions, funnels, retention, sources, pages, and events. Expose filters by date, environment, device, country, referrer, and selected properties. Add retention controls, raw-event export, deletion, health checks, and backup instructions. Include clear empty, loading, success, and recoverable error states. Add input validation, safe filenames, and graceful handling of unavailable APIs. Write focused tests for the core transformation and one end-to-end happy path. Create a README with setup, architecture, permissions, data location, and backup steps. Do not add accounts, billing, telemetry, analytics, or a hosted control plane. Do not claim to reproduce proprietary data, network liquidity, regulated access, or frontier infrastructure. Deliberately leave out cross-site identity graphs. Deliberately leave out session replay and automatic DOM capture. Deliberately leave out warehouse-scale reverse ETL and enterprise governance. Finish by running the tests and listing the exact commands used. ## Boundaries Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors. ## Production baseline - Configuration: validated at startup with safe local defaults where possible. - Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts. - Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test. ## Decision records For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it. ===== AGENTS.md ===== # Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone. ===== MILESTONES.md ===== # Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations. ===== OPERATIONS.md ===== # Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted Mixpanel capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
# Mixpanel indie build ## Goal Build the smallest trustworthy replacement for the core Mixpanel workflow for one developer or a tiny team. ## Scope Collect a small transparent stream of privacy-conscious first-party events, build funnels and retention views locally, answer a small set of product questions, and retain raw data under the owner's control. ## Quick start 1. Install the documented dependencies. 2. Copy `.env.example` to `.env`. 3. Run the development command chosen during implementation. 4. Complete the acceptance checks in `BUILD_PLAN.md`. ## Honest limits This build deliberately does not replace: - large-scale ingestion, identity handling, query engine, governance, and product expertise - identity stitching - session replay - warehouse connectors - high-volume global ingestion and support If those capabilities are essential, use Umami instead of pretending the gap is solved.
# Agent instructions - Optimize for a working, understandable weekend build. - Prefer the fewest moving parts that satisfy the brief. - Do not invent cryptography, security guarantees, APIs, or compliance claims. - Keep secrets out of source control and logs. - Add focused tests for destructive, security-sensitive, and data-loss paths. - Run the project checks before declaring the build complete. - Record any deliberate shortcut in the README under "Tradeoffs".
# Build plan ## Original build brief Build a closest honest personal substitute for Mixpanel in an empty repository. Use Next.js 15, TypeScript, ClickHouse, PostgreSQL, and Docker Compose; do not offer alternative stacks. The core loop is: collect a small transparent stream of privacy-conscious first-party events, build funnels and retention views locally, answer a small set of product questions, and retain raw data under the owner's control. Make the first run work locally with one documented command. Store all user data locally by default and make export straightforward. Put secrets in .env, ship .env.example, and never commit credentials. Ship a lightweight browser SDK for page views and explicit custom events. Create projects, API keys, environments, event names, and a documented event schema. Ingest idempotently, filter obvious bots, truncate IP data, and avoid fingerprinting. Build dashboards for visitors, sessions, funnels, retention, sources, pages, and events. Expose filters by date, environment, device, country, referrer, and selected properties. Add retention controls, raw-event export, deletion, health checks, and backup instructions. Include clear empty, loading, success, and recoverable error states. Add input validation, safe filenames, and graceful handling of unavailable APIs. Write focused tests for the core transformation and one end-to-end happy path. Create a README with setup, architecture, permissions, data location, and backup steps. Do not add accounts, billing, telemetry, analytics, or a hosted control plane. Do not claim to reproduce proprietary data, network liquidity, regulated access, or frontier infrastructure. Deliberately leave out cross-site identity graphs. Deliberately leave out session replay and automatic DOM capture. Deliberately leave out warehouse-scale reverse ETL and enterprise governance. Finish by running the tests and listing the exact commands used. ## Required capabilities - Docker - ClickHouse - PostgreSQL - public HTTPS collector endpoint - site script access ## Delivery order 1. Scaffold the smallest runnable application and document its commands. 2. Implement the primary data model and core workflow. 3. Add validation, safe failure states, and persistence. 4. Cover the critical path with automated tests. 5. Exercise a clean install from the README and fix every missing step. ## Done when - A new user can go from clone to first successful workflow using only the README. - The core workflow works without paid infrastructure unless the brief requires it. - Tests cover the highest-risk behavior. - Known limitations are explicit rather than hidden.
# Copy to .env and document every variable when it is introduced. # Never put real credentials in this file. APP_ENV=development # Add only values required by the selected implementation.
# Mixpanel product brief ## Problem A consolation build is possible, but the paid product's decisive value sits outside a solo rebuild. For Mixpanel, collect a small transparent event stream and build funnels and retention locally. The hard boundary is large-scale ingestion, identity handling, query engine, governance, and product expertise, plus data pipeline reliability and analytical depth. ## Product outcome Collect a small transparent stream of privacy-conscious first-party events, build funnels and retention views locally, answer a small set of product questions, and retain raw data under the owner's control. ## Target user A serious builder who needs a maintainable product foundation rather than a one-off demo. ## Required capabilities - Docker - ClickHouse - PostgreSQL - public HTTPS collector endpoint - site script access ## Explicit non-goals for v1 - large-scale ingestion, identity handling, query engine, governance, and product expertise - identity stitching - session replay - warehouse connectors - high-volume global ingestion and support ## Success criteria - The primary workflow is measurable end to end. - Setup is reproducible in a clean environment. - Failure, recovery, and support paths are documented. - Product claims match what the implementation actually guarantees.
# Architecture ## Starting brief Build a closest honest personal substitute for Mixpanel in an empty repository. Use Next.js 15, TypeScript, ClickHouse, PostgreSQL, and Docker Compose; do not offer alternative stacks. The core loop is: collect a small transparent stream of privacy-conscious first-party events, build funnels and retention views locally, answer a small set of product questions, and retain raw data under the owner's control. Make the first run work locally with one documented command. Store all user data locally by default and make export straightforward. Put secrets in .env, ship .env.example, and never commit credentials. Ship a lightweight browser SDK for page views and explicit custom events. Create projects, API keys, environments, event names, and a documented event schema. Ingest idempotently, filter obvious bots, truncate IP data, and avoid fingerprinting. Build dashboards for visitors, sessions, funnels, retention, sources, pages, and events. Expose filters by date, environment, device, country, referrer, and selected properties. Add retention controls, raw-event export, deletion, health checks, and backup instructions. Include clear empty, loading, success, and recoverable error states. Add input validation, safe filenames, and graceful handling of unavailable APIs. Write focused tests for the core transformation and one end-to-end happy path. Create a README with setup, architecture, permissions, data location, and backup steps. Do not add accounts, billing, telemetry, analytics, or a hosted control plane. Do not claim to reproduce proprietary data, network liquidity, regulated access, or frontier infrastructure. Deliberately leave out cross-site identity graphs. Deliberately leave out session replay and automatic DOM capture. Deliberately leave out warehouse-scale reverse ETL and enterprise governance. Finish by running the tests and listing the exact commands used. ## Boundaries Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors. ## Production baseline - Configuration: validated at startup with safe local defaults where possible. - Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives. - Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions. - Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts. - Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists. - Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test. ## Decision records For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it.
# Agent instructions - Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code. - Implement milestone by milestone; keep each change reviewable and leave the application runnable. - Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present. - Never invent cryptography or silently weaken a requirement to make a test pass. - Use provider interfaces for external services and deterministic fakes in tests. - Add migrations and rollback or recovery notes for persistent data changes. - Log useful operational context without credentials, tokens, passwords, or personal data. - Update documentation and run all checks before completing a milestone.
# Delivery milestones ## M0 — Decisions and scaffold - Confirm the runtime, persistence model, threat boundaries, and deployment target. - Create a reproducible local environment and continuous checks. ## M1 — Core workflow - Implement the smallest end-to-end product path with validation and tests. - Keep integrations behind interfaces. ## M2 — Trust layer - Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards. - Test abuse cases and destructive operations. ## M3 — Operability - Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration. ## M4 — Release gate - Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise. - Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations.
# Operations ## Before release - Validate configuration and secrets at startup. - Define backup, restore, and rollback procedures and test them. - Document logs, error tracking, health signals, and alert ownership. - Set dependency update and vulnerability review expectations. ## Incident checklist 1. Contain the issue without destroying evidence or user data. 2. Record the timeline and affected scope. 3. Rotate exposed secrets and revoke compromised sessions or credentials. 4. Restore from a verified source when needed. 5. Document the root cause, remediation, and regression test. ## Launch constraint Do not market omitted Mixpanel capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.
$ choose a build depth, inspect the files, then open the complete pack in your agent · this prompt is generated from the build plan · improve it via PR
People still pay for Mixpanel because teams pay because analytics must keep collecting and remain trustworthy while the product changes underneath it. The recurring cost buys event schemas, bot filtering, identity, late data, retention, query cost, privacy, backups, and always-on ingestion, not just the visible interface.
xlarge-scale ingestion, identity handling, query engine, governance, and product expertise
xidentity stitching
xsession replay
xwarehouse connectors
xhigh-volume global ingestion and support
Don't feel like building it? These folks already made it free.
all 3 free alternatives to Mixpanel →· no votes, no pay-to-list · just what's real
Mixpanel pricing
| plan | monthly | annual (per mo) | what you get |
|---|---|---|---|
| free | $0/workspace | $0/workspace | 1,000,000 events/month, 10,000 session replays/month, 5 saved reports per seat, 30 Spark AI queries/month, and unlimited seats |
| growth | $0/workspace | — | First 1,000,000 events/month free; selectable through 20 million events/month, 20,000 session replays/month included and configurable up to 500,000, 60 Spark AI queries/month, unlimited reports and seats |
| enterprise | custom | — | Up to 1 trillion events/month, customizable session-replay volume, 300 Spark AI queries/month, and unlimited seats/reports |
free tier1,000,000 events/month, 10,000 session replays/month, 5 saved reports per seat, 30 Spark AI queries/month, and unlimited seats
billingmonthly + annual; annual Growth requires more than 1 million events/month committed; card charged at the start of each billing period
hidden costsGrowth has no billing cap: overages on the 1M-event plan are $0.00028/event and billed next month. Group Analytics adds 40% and Data Pipelines adds 20% to overage charges; Metric Trees, experiments/feature flags, account analytics, pipelines, and some support are add-ons.
verified 2026-08-12 · source ↗
Vibecode Mixpanel
Not really. Mixpanel's value is not the code: Recheck price before merge. See the honest breakdown above.
How much does Mixpanel cost?
Mixpanel's pricing is usage-based or varies by plan · Growth pricing is usage based; canonical monthly amount is null..
What do I lose by replacing Mixpanel?
Honestly: large-scale ingestion, identity handling, query engine, governance, and product expertise; identity stitching; session replay; warehouse connectors; high-volume global ingestion and support. If any of those are load-bearing for you, keep paying.
Is there an open-source alternative to Mixpanel?
Yes: Umami (Funnels, cohorts and retention locally, without the enterprise taxonomy workshop.) PostHog (Funnels, cohorts and retention with a free million-event runway and considerably more machinery.) OpenPanel (The useful product-analytics core, plus a ClickHouse stack you now get to know personally.) All 3 curated free alternatives are at vibecodeit.com/mixpanel/alternatives. The prompt is for when you want it exactly your way.