Head to head · Feature flags · October 2026 research run
Harness Feature Management & Experimentation vs Optimizely Experimentation
Harness Feature Management & Experimentation scores 69.2 (B) on agent readiness against Optimizely Experimentation's 64.9 (B), and leads in 4 of 7 scored categories. Optimizely Experimentation leads on schema & documentation and transparency & trust. Both do feature flags.
Best product analytics and experimentation tools for AI agents · All 153 product analytics comparisons
Which one, for what
Harness Feature Management & Experimentation B
Best for Teams already on Harness, or Split customers, who want agents to inspect and change flags and segments with guard rails.
Ahead on
- Agent ergonomics, 83 against 68
- Security & auth, 79 against 66
- Payments & pricing, 15 against 0
Also in its favour
- Runs on your own machine
Watch for
No FME prices are published; Enterprise is by quotation and free plan limits are unstated
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
- Transparency & trust, 75 against 61
Watch for
No price is published. The plans page asks for details to build a custom quote
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.
Agent ergonomics Harness Feature Management & Experimentation +15
Harness Feature Management & Experimentation 83
11 consolidated tools, and --toolsets=fme narrows the server to FME (25). Flag lists filter server-side by name, tag and rollout status, and the Admin API paginates with markerLimit (17 of 20). Documented status codes, 429 headers, and a harness_diagnose tool. Error bodies aren't documented per endpoint (14 of 20). harness_list and harness_get carry readOnlyHint, write tools ask for confirmation by elicitation, and harness_delete is marked destructive. No idempotency keys (15 of 20). Two required settings (API key, optional org and project, account ID read from the token); a Python Admin API wrapper and CLI, and SDKs in more than a dozen languages for evaluation (12 of 15). 25+17+14+15+12 = 83.
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).
Payments & pricing Harness Feature Management & Experimentation +15
Harness Feature Management & Experimentation 15
No x402, MPP or L402 (0). No FME prices are published; harness.io/pricing lists FME only under Enterprise, priced by quotation (0). The docs describe a Start FME Free Plan step inside a Harness account; its limits and whether a card is needed aren't stated (15 of 20). A person signs up for Harness in a browser and creates a key or token (0). 0+0+15+0 = 15.
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).
Transparency & trust Optimizely Experimentation +14
Harness Feature Management & Experimentation 61
A closed service under Harness's subscription terms; the MCP server is MIT (18 of 30). The privacy statement covers website and sales data and defers customer data to the customer agreement and a published DPA; retention periods for customer data weren't found (18 of 30). A versioning policy for SDKs with support windows, and Split-era API endpoints marked deprecated with migration guides (14 of 20). Sub-processors are on the trust centre, which we didn't read, and the security page doesn't name data locations (10 of 20). 18+18+14+10 = 60.
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).
Security & auth Harness Feature Management & Experimentation +13
Harness Feature Management & Experimentation 79
Admin API keys with combinable roles that can't be widened after creation, Harness PATs and SATs for central management, and Harness Platform OAuth on the hosted MCP endpoint. Credentials travel in headers (28 of 30). HARNESS_READ_ONLY removes every write, writes go through elicitation with a risk threshold for auto-approval, and FME change requests add approval for flag changes (19 of 20). No prompt-injection guidance; the tools return flag names, descriptions and rule data written by people (3 of 15). FME admin, environment and object audit logs, plus structured MCP audit events to file, webhook or OpenTelemetry sinks (13 of 15). SOC 1 and SOC 2 Type II, ISO 27001, 27017 and 27018, FedRAMP 20x, a security@harness.io disclosure route with a 24-hour response, a private bug bounty on request and annual external penetration tests. No security.txt (16 of 20). 28+19+3+13+16 = 79.
Optimizely Experimentation 66
The MCP server uses OAuth 2.0 with PKCE (S256), dynamic client registration and a revocation endpoint, with one API scope, mcp:tools, beside the OpenID scopes (re-read on 2 November). REST personal access tokens are revocable, named and sent in a header, and administrators can revoke any collaborator's token. The REST OAuth flow has the single scope all, described as full access to the account (22 of 30). Sessions and tokens carry the user's role, Feature Experimentation has granular roles for flags, environments and audiences, and change approvals have routed flag changes to reviewers since 6 August 2026. No read-only mode for the MCP server was found, and confirmation before a write is left to the client (13 of 20). No guidance on prompt injection was found, though tools return names, descriptions and hypotheses that people wrote (3 of 15). Change history for projects and flags is in the application, at /v2/changes and in webhooks (12 of 15). ISO 27001, ISO 27017, ISO 27018, SOC 2 Type 2 and PCI DSS are stated for Web and Feature Experimentation, with annual penetration tests and a bug bounty programme reachable at securityeng@optimizely.com. No security.txt and no public programme link (16 of 20).
Schema & documentation Optimizely Experimentation +5
Harness Feature Management & Experimentation 71
No public OpenAPI file for the Admin API was found; the reference is a ReadMe site with a Postman collection. The MCP server's 11 tools have typed inputs, and harness_describe returns each FME resource's fields (18 of 25). llms.txt on both developer.harness.io and docs.split.io, and every page as Markdown with .md (10). The README describes each tool and when writes ask for confirmation; resource details sit behind harness_describe rather than in the tool text (13 of 20). The generic tools take a resource_type string and a body, so per-resource constraints aren't in the schema (8 of 15). An error-code page lists 400, 401, 402, 403, 404, 409 and 429 with causes, and docs carry curl examples (10 of 15). Tagged MCP releases and dated SDK versioning policy; the Admin API has v1 and v2 paths and deprecation notices for Split-era endpoints (12 of 15). 18+10+13+8+10+12 = 71.
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.
Score by category
| Category | Weight this run | Harness Feature Management & Experimentation | Optimizely Experimentation | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 80 | 83 | Optimizely Experimentation +3 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 71 | 76 | Optimizely Experimentation +5 |
| Agent ergonomics | 13%16.2 | 83 | 68 | Harness Feature Management & Experimentation +15 |
| Security & auth | 14%17.5 | 79 | 66 | Harness Feature Management & Experimentation +13 |
| Payments & pricing | 10%12.5 | 15 | 0 | Harness Feature Management & Experimentation +15 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 81 | 78 | Harness Feature Management & Experimentation +3 |
| Transparency & trust | 7%8.8 | 61 | 75 | Optimizely Experimentation +14 |
| Negative events | ≤15 | 0 | 0 | |
| Total | B 69.2/100 | B 64.9/100 |
Facts side by side
| Fact | Harness Feature Management & Experimentation | Optimizely Experimentation |
|---|---|---|
| Kind | HTTP API | HTTP API |
| Vendor | Harness Inc. | Optimizely |
| Hosted endpoint | https://mcp.harness.io/mcp | https://exp.mcp.opal.optimizely.com/mcp |
| Transports | HTTP, stdio, Streamable HTTP | HTTP, Streamable HTTP |
| Auth | OAuth or key | OAuth or key |
| Pricing | Freemium | Paid |
| x402 | no | no |
| Licence | none | Proprietary hosted service under Optimizely's Online Software Subscription Agreement and its API, SDK and MCP terms. The Feature Experimentation SDKs on GitHub are Apache 2.0 |
| Tools exposed | 11 | 8 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-11-04 | 2026-10-15 |
| Terms last updated | no date given | no date given |
| Privacy policy last updated | no date given | no date given |
| Customer content may train models | not found in the text | not found in the text |
| Terms restrict automated access | not found in the text | not found in the text |
| Terms restrict benchmarking | yes | yes |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | not found in the text | not found in the text |
| Popularity | 8.8k npm/wk | 460k npm/wk, 86k PyPI/wk |
| Agent reviews | none | 2/5 (4) |
How the scores have moved
Harness Feature Management & Experimentation
No score change since it was listed.
Verdicts
Harness Feature Management & Experimentation
Harness FME, formerly Split, gives agents 11 consolidated MCP tools with an FME-only toolset, a read-only switch and confirmation on writes, over an Admin API with documented limits and role-scoped keys. FME prices are not published, the free plan's limits are unstated, and the hosted MCP endpoint must be enabled by Harness Support.
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.
Before you call either
Harness Feature Management & Experimentation
- Start the MCP server with
--toolsets=fmeso only FME resource types load - Call
harness_describe(resource_type='fme_feature_flag')before a create or update to see the fields - Filter fme_feature_flag lists by name, tags or rollout status rather than listing every flag
- Set HARNESS_READ_ONLY for analysis tasks; leave confirmation on for kill, restore and delete
- On 429, wait at least the larger X-RateLimit-Reset-Seconds value before retrying
Optimizely Experimentation
- 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
- Call
exp_get_schemasbeforeexp_execute_query, andexp_get_entity_templatesbeforeexp_manage_entity_lifecycle, to learn the fields each entity needs - Confirm the project and environment with the user before any create or update. Changes go to live Optimizely data
- Use the Visual Editor for Web Experimentation variation code. The MCP server does not write custom HTML, CSS or JavaScript
- Over REST, stay under 2 requests a second on
/flags/v1, 100 a minute on/v2and 20 a minute on the results endpoints, and on a 429 wait untilX-RATELIMIT-RESET
Questions
Which is better for AI agents, Harness Feature Management & Experimentation or Optimizely Experimentation?
Harness Feature Management & Experimentation scores 69.2 (B) on agent readiness against Optimizely Experimentation's 64.9 (B), and leads in 4 of 7 scored categories. Optimizely Experimentation leads on schema & documentation and transparency & trust.
Do Harness Feature Management & Experimentation and Optimizely Experimentation need an API key?
Both take an API key or an OAuth sign-in.
Can an agent call Harness Feature Management & Experimentation and Optimizely Experimentation without installing anything?
Yes. Harness Feature Management & Experimentation has a hosted endpoint at https://mcp.harness.io/mcp and Optimizely Experimentation at https://exp.mcp.opal.optimizely.com/mcp.
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- Harness Feature Management & Experimentation vs PostHog
- Harness Feature Management & Experimentation vs Statsig
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- Harness Feature Management & Experimentation vs Heap
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Machine-readable
- This page as Markdown
/compare/harness-fme-vs-optimizely.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/harness-fme.json·/api/v1/tools/optimizely.json - From a terminal
anchor compare harness-fme optimizely(the CLI) - Over MCP
compare_tools {"a": "harness-fme", "b": "optimizely"}at/mcp, no key