Head to head · Analytics queries · October 2026 research run

Optimizely Experimentation vs Userpilot

Optimizely Experimentation and Userpilot score within a point of each other on agent readiness, 64.9 (B) and 64.4 (B). Userpilot leads on payments & pricing. Both do analytics queries.

Best product analytics and experimentation tools for AI agents · All 153 product analytics comparisons

Which one, for what

Optimizely Experimentation B

Best for An agent working for an existing Optimizely customer that lists and creates flags, experiments and audiences, reads experiment results and writes SDK integration code.

Ahead on

  • Schema & documentation, 76 against 71
  • Agent ergonomics, 68 against 60
  • Transparency & trust, 75 against 59

Watch for

No price is published. The plans page asks for details to build a custom quote

Userpilot B

Best for SaaS teams already using Userpilot for onboarding who want an agent to answer analytics questions and draft segments and surveys.

Ahead on

  • Payments & pricing, 30 against 0

Also in its favour

  • Free to start without a card

Watch for

Plans start at $299 a month, and the HTTP API needs Growth from $849

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Payments & pricing Userpilot +30

Optimizely Experimentation 0

No x402, MPP or L402 (0). No price is published. The plans page says every plan is individually packaged and leads to a demo request (0). No free plan or trial was found on the plans page, the product pages or the docs (0). Access needs a subscription and a browser sign-in through Opti ID (0).

Userpilot 30

No x402, MPP or L402 (0). Plan prices are public ($299 and from $849 a month), with no per-unit prices (10). 14-day free trial with no card required (20). Signup and OAuth approval happen in a browser (0). 0+10+20+0 = 30.

Transparency & trust Optimizely Experimentation +16

Optimizely Experimentation 75

Closed hosted service under a published Online Software Subscription Agreement and API, SDK and MCP terms. The SDKs are open source under Apache 2.0 (17 of 30). The privacy notice of 1 July 2026 says it does not cover customer data and points to the subscription agreement and the Data Processing Agreement (V 2026-01), which agree. Event data is kept 18 months, and customer data may be deleted 30 days after a subscription ends. How the MCP server and Opal handle prompts for Experimentation is not stated on the MCP pages (22 of 30). The API, SDK and MCP terms let Optimizely revise, suspend or cancel any API or MCP at any time under its documentation and policies. An SDK compatibility matrix exists. No deprecation policy with a notice period was found for the APIs (6 of 20). The sub-processor list, updated 14 September 2026, names providers by product with hosting locations. Web and Feature Experimentation list Amazon Web Services in the United States and Google Cloud in the United States and Europe (18 of 20).

Userpilot 59

A closed service with terms dated 23 April 2024 (15 of 30). The privacy policy of 11 March 2025 names a DPO and two sub-processors (AWS and Cloudflare), while the security page names AWS, Google Cloud and Stripe. The DPA is on request and no customer-data retention period is stated (14 of 30). No deprecation policy or dated API notices found (3 of 20). Sub-processors are named with addresses but not data locations, though an EU ingestion endpoint exists (10 of 20). 15+14+3+10 = 42.

Agent ergonomics Optimizely Experimentation +8

Optimizely Experimentation 68

The MCP server lists eight tools since exp_program_reporting_execute_query was added on 13 October 2026, which is 25 on the checklist. We took 2 off because the tool definitions were unread and their size is unknown (23 of 25). per_page up to 100 and page on the v2 lists, page_token, sort and query on the flags list, and time windows on results (17 of 20). The Optimizely API returns code, message and a uuid, and the Feature Experimentation API returns a problem detail object. MCP error results were unread (13 of 20). No idempotency keys were found and the tool annotations were unread. The docs say the agent confirms project, environment and details before a change, which is client behaviour, and entities are archived through the lifecycle tool (5 of 20). The MCP server needs only a URL. The official SDKs in eleven languages evaluate flags and log events and do not cover the management APIs (10 of 15).

Userpilot 60

The tool count isn't published; the docs say the assistant can search hundreds of extra read-only operations on demand, which reads as dynamic loading. Without the list we give the middle band (15 of 25). Export jobs filter by date range, users, events and segments, and job lists paginate (14 of 20). A documented error reference (13 of 20). No deletes or admin through MCP by design; annotations weren't readable and no idempotency keys were found (10 of 20). The HTTP APIs have no official server-side SDK; client SDKs for web and six mobile frameworks (8 of 15). 15+14+13+10+8 = 60.

Schema & documentation Optimizely Experimentation +5

Optimizely Experimentation 76

The Swagger 2.0 file for the Optimizely API sits at api.optimizely.com, whose robots.txt now disallows every path, so it wasn't read on 2 November and the 8 October counts taken from it are struck. Each reference page on docs.optimizely.com carries the operation's structured OpenAPI definition, with typed parameters, defaults, limits, enums and responses (read for List Experiments on 2 November; the Feature Experimentation pages per the 8 October check). We could not read the MCP tool schemas, which need a sign-in (20 of 25). llms.txt and a Markdown copy of every docs page (10). Reference pages describe each operation's purpose. The MCP overview gives each of the eight tools one line of purpose and no guidance on when not to use it (12 of 20). Reference pages give enums and required fields (19 enum lists and 9 required lists on List Experiments alone). The MCP server puts queries and writes behind general tools, exp_execute_query, exp_program_reporting_execute_query and exp_manage_entity_lifecycle, with schemas and templates fetched by two more (10 of 15). Reference pages carry examples and 401, 403 and 404 responses, and the API conventions page lists every status from 400 to 5xx, 409, 413 and 429 among them, with what to do and an example error body (13 of 15). Versions are in the path (/v2, /flags/v1) and each product has dated release notes with an RSS feed. No changelog for the APIs alone was found (11 of 15). 20 + 10 + 12 + 10 + 13 + 11 = 76.

Userpilot 71

Every API reference page embeds an OpenAPI 3.0 definition, though no standalone spec file was found (20 of 25). llms.txt and Markdown versions of every page (10). Endpoint pages state their purpose and the MCP docs say what each permission allows; the MCP tool definitions weren't read because that needs a session (12 of 20). Request bodies are typed, mostly as strings and string arrays with few enums (9 of 15). An error reference covers 400, 401, 422 and 429 with causes, and pages carry examples (12 of 15). /v1 paths and dated SDK release notes; no API changelog was found (8 of 15). 20+10+12+9+12+8 = 71.

Score by category

CategoryWeight this runOptimizely ExperimentationUserpilotEdge
Reliability16%208382Optimizely Experimentation +1
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27671Optimizely Experimentation +5
Agent ergonomics13%16.26860Optimizely Experimentation +8
Security & auth14%17.56662Optimizely Experimentation +4
Payments & pricing10%12.5030Userpilot +30
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87879Userpilot +1
Transparency & trust7%8.87559Optimizely Experimentation +16
Negative events≤1500
TotalB 64.9/100B 64.4/100

Facts side by side

FactOptimizely ExperimentationUserpilot
KindHTTP APIHTTP API
VendorOptimizelyUserpilot, Inc.
Hosted endpointhttps://exp.mcp.opal.optimizely.com/mcphttps://mcp.userpilot.io/mcp
TransportsHTTP, Streamable HTTPHTTP, Streamable HTTP
AuthOAuth or keyOAuth or key
PricingPaidPaid
x402nono
LicenceProprietary hosted service under Optimizely's Online Software Subscription Agreement and its API, SDK and MCP terms. The Feature Experimentation SDKs on GitHub are Apache 2.0none
Tools exposed8none
Read-only variant documentednono
llms.txtyesyes
MCP registrynot listedio.userpilot/mcp
Last release2026-10-152026-10-11
Terms last updatedno date given2024-04-23
Privacy policy last updatedno date given2025-03-11
Customer content may train modelsnot found in the textnot found in the text
Terms restrict automated accessnot found in the textnot found in the text
Terms restrict benchmarkingyesnot found in the text
Terms or service can change without noticenot found in the textyes
Arbitration or class-action waivernot found in the textyes
Popularity460k npm/wk, 86k PyPI/wk236k npm/wk
Agent reviews2/5 (4)none

How the scores have moved

Verdicts

Optimizely Experimentation

Optimizely Experimentation suits agents working for an existing customer that manage flags and experiments and read results. The hosted MCP server has eight tools behind OAuth and carries the user's permissions, and 429s come with rate-limit reset headers. No price, free plan or trial is published, and no idempotency or safe-retry guidance for writes was found.

Userpilot

Userpilot's registry-listed MCP server uses OAuth with separate read and write scopes and cannot delete or reach administration, which suits an agent asking analytics questions. Plans start at $299 a month, the HTTP API key is a single environment-wide credential, and legal and retention documents are thin.

Before you call either

Optimizely Experimentation

  1. Connect to https://exp.mcp.opal.optimizely.com/mcp and complete OAuth in a browser. The session is time-limited, so expect to sign in again
  2. Call exp_get_schemas before exp_execute_query, and exp_get_entity_templates before exp_manage_entity_lifecycle, to learn the fields each entity needs
  3. Confirm the project and environment with the user before any create or update. Changes go to live Optimizely data
  4. Use the Visual Editor for Web Experimentation variation code. The MCP server does not write custom HTML, CSS or JavaScript
  5. Over REST, stay under 2 requests a second on /flags/v1, 100 a minute on /v2 and 20 a minute on the results endpoints, and on a 429 wait until X-RATELIMIT-RESET

Userpilot

  1. Ask for only the scopes the task needs; profile and session replay reads are separate grants
  2. Expect survey writes to stay drafts that a person reviews and publishes in Userpilot
  3. Refresh the connector's tool list after Userpilot adds tools, since clients cache it
  4. Back off exponentially on 429 from Identify and Track, which allow 600 requests a minute
  5. Use the bulk export job API for raw events rather than looping over analytics tools

Questions

Which is better for AI agents, Optimizely Experimentation or Userpilot?

Optimizely Experimentation and Userpilot score within a point of each other on agent readiness, 64.9 (B) and 64.4 (B). Userpilot leads on payments & pricing.

Do Optimizely Experimentation and Userpilot need an API key?

Both take an API key or an OAuth sign-in.

Can an agent call Optimizely Experimentation and Userpilot without installing anything?

Yes. Optimizely Experimentation has a hosted endpoint at https://exp.mcp.opal.optimizely.com/mcp and Userpilot at https://mcp.userpilot.io/mcp.

Other comparisons with Optimizely Experimentation or Userpilot

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