# Harness Feature Management & Experimentation vs Mostly Good Metrics

> Harness Feature Management & Experimentation scores 69.2 (B) to Mostly Good Metrics's 41.7 (E) for feature flags and experiments. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/harness-fme-vs-mostly-good-metrics
- Markdown: https://www.anchorterminal.com/compare/harness-fme-vs-mostly-good-metrics.md (~5,000 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-07

Harness Feature Management & Experimentation scores 69.2 (B) on agent readiness against Mostly Good Metrics's 41.7 (E), and leads in 6 of 7 scored categories. Mostly Good Metrics leads on payments & pricing. Both do feature flags and experiments.

- Harness Feature Management & Experimentation: grade B, 69.2/100, rank #257 of 1486. Markdown https://www.anchorterminal.com/tools/harness-fme.md · JSON https://www.anchorterminal.com/api/v1/tools/harness-fme.json
- Mostly Good Metrics: grade E, 41.7/100, rank #1277 of 1486. Markdown https://www.anchorterminal.com/tools/mostly-good-metrics.md · JSON https://www.anchorterminal.com/api/v1/tools/mostly-good-metrics.json
- Best product analytics and experimentation tools for AI agents: https://www.anchorterminal.com/best/product-analytics/index.md
- All 153 product analytics comparisons: https://www.anchorterminal.com/compare/product-analytics/index.md

## Which one, for what

### Harness Feature Management & Experimentation (B)

Good for: Teams already on Harness, or Split customers, who want agents to inspect and change flags and segments with guard rails.

Ahead on:
- Reliability, 80 against 29
- Schema & documentation, 71 against 49
- Agent ergonomics, 83 against 49
- Security & auth, 79 against 33
- Maintenance & community, 81 against 74
- Transparency & trust, 61 against 45

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

### Mostly Good Metrics (E)

Good for: Indie and small-team apps that want simple funnels and retention an agent can query.

Ahead on:
- Payments & pricing, 30 against 15

Also in its favour:
- Free to start without a card

Watch for: Public beta run by one developer, with no named legal entity in the terms


## Why the edge

### Reliability: Harness Feature Management & Experimentation +51

- Harness Feature Management & Experimentation (80): Graded on the hosted FME Admin API with the hosted lines. Statuspage at status.harness.io with an FME component among 196 (20). In the 90 days from 8 August, two FME incidents: API write operations returned 499 errors for 30 minutes on 20 August (minor) and the FME user interface was unavailable for 15 minutes on 23 August (major, interface only; flag evaluation was unaffected per the post). No API outage of an hour or more (20 of 30). About 20 Admin API requests per 10 seconds per organisation and per IP, documented on the MCP page (15). 429 responses carry remaining and reset headers with guidance to wait for the larger reset, and the MCP server backs off and retries three times (15). No SLA was found on harness.io/pricing or the FME docs (0). FME is generally available and the MCP server is at 3.2.40 (10). 20+20+15+15+0+10 = 80.
- Mostly Good Metrics (29): Graded on the hosted service with the hosted lines. No status page was found (0) and no incident history could be read (5). Ingestion limits are documented per plan (1,000 to 100,000 events a minute and 10,000 to 1,000,000 an hour), but no limit for MCP or query calls was found (12 of 15). 429 with Retry-After in the header and body, and the SDKs queue events and back off. No idempotency or safe-retry guidance for writes (12 of 15). No SLA (0). The press kit calls the product a public beta (0). 0+5+12+12+0+0 = 29.

### Security & auth: Harness Feature Management & Experimentation +46

- 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.
- Mostly Good Metrics (33): OAuth 2.0 with PKCE, dynamic client registration and a revocation endpoint for MCP and the CLI; project ingest keys in a Bearer header that can be pinned to origins or app IDs. The only tool scope advertised is mcp:tools, so a connection gets every tool the user can use (24 of 30). Restricted keys and a confirmation step for unrestricted keys in the CLI; no read-only MCP mode or approval for deletes was found (6 of 20). Event properties come from apps and end users and reach the agent, and no prompt-injection guidance was found (3 of 15). No audit log was found (0). No security.txt, disclosure policy or certification was found (0). 24+6+3+0+0 = 33.

### Agent ergonomics: Harness Feature Management & Experimentation +34

- 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.
- Mostly Good Metrics (49): 53 tools, more than 30 (5). We added 3 because Goals and Alerts tools load only where enabled and query_metrics batches up to 10 queries (8 of 25). Date ranges, grouping and filters on queries; no documented page or limit parameters for lists (12 of 20). JSON errors with a message, and per-item status in batch results (13 of 20). Annotations weren't readable without a session, the tool list includes deletes and key revocation, and no idempotency keys were found (4 of 20). Five client SDKs and a CLI with `--json` output (12 of 15). 8+12+13+4+12 = 49.

### Schema & documentation: Harness Feature Management & Experimentation +22

- 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.
- Mostly Good Metrics (49): No OpenAPI file was found. The docs say every MCP tool describes its own parameters, and the query definition object is documented in full; we didn't open an MCP session to read the schemas (12 of 25). No llms.txt (404) and no Markdown pages served for agents (0). Each tool area is documented with examples, and the docs say when to use query_metrics instead of repeated execute_query calls (10 of 20). The query definition lists metrics, dimensions, date ranges and filter operators (9 of 15). The ingestion API documents its error body and status codes, and query_metrics reports per-item errors (11 of 15). /v1 and /api/v2 paths and dated SDK tags, but no product changelog (7 of 15). 12+0+10+9+11+7 = 49.

### Transparency & trust: Harness Feature Management & Experimentation +16

- 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.
- Mostly Good Metrics (45): The service is closed; the SDKs and CLI are MIT. Terms of December 2025 with no legal entity named (18 of 30). The privacy policy and terms agree on raw-event retention for the subscription's life and deletion within 14 days of account deletion; the about page says data is not used to train models. No DPA was found (18 of 30). The legacy X-MGM-Key header is still supported, and no deprecation policy was found (3 of 20). The terms name eight sub-processors with their purpose, without data locations (12 of 20). 18+18+3+12 = 51.

### Payments & pricing: Mostly Good Metrics +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.
- Mostly Good Metrics (30): No x402, MPP or L402 (0). Plan prices with event allowances are on the home page; no per-event price (10). Free plan with no card, stated on the home and about pages (20). Signup and OAuth approval happen in a browser (0). 0+10+20+0 = 30.

## Score by category

| Category | Weight | Harness Feature Management & Experimentation | Mostly Good Metrics | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 80 | 29 | Harness Feature Management & Experimentation +51 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 71 | 49 | Harness Feature Management & Experimentation +22 |
| Agent ergonomics | 13% (16.2 this run) | 83 | 49 | Harness Feature Management & Experimentation +34 |
| Security & auth | 14% (17.5 this run) | 79 | 33 | Harness Feature Management & Experimentation +46 |
| Payments & pricing | 10% (12.5 this run) | 15 | 30 | Mostly Good Metrics +15 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 81 | 74 | Harness Feature Management & Experimentation +7 |
| Transparency & trust | 7% (8.8 this run) | 61 | 45 | Harness Feature Management & Experimentation +16 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **69.2 · B** | **41.7 · E** | |

## Facts side by side

| Fact | Harness Feature Management & Experimentation | Mostly Good Metrics |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Harness Inc. | Mostly Good Metrics |
| Hosted endpoint | `https://mcp.harness.io/mcp` | `https://app.mostlygoodmetrics.com/mcp` |
| Transports | HTTP, stdio, Streamable HTTP | HTTP, Streamable HTTP |
| Auth | OAuth or key | OAuth or key |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| Tools exposed | 11 | 53 |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-11-04 | 2026-10-16 |
| Terms last updated | no date given | 2025-12-01 |
| Privacy policy last updated | no date given | 2025-12-01 |
| 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 | not found in the text |
| 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 | 81 npm/wk |

## 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.

**Mostly Good Metrics.** Mostly Good Metrics lets an agent run ad-hoc funnels, retention and up to ten metric queries per call through a hosted MCP server with OAuth, at prices from $0. It is a public beta built by one developer, with no status page, no named legal entity and no security policy found.

## Before you call either

### Harness Feature Management & Experimentation

1. Start the MCP server with `--toolsets=fme` so only FME resource types load
2. Call `harness_describe(resource_type='fme_feature_flag')` before a create or update to see the fields
3. Filter fme_feature_flag lists by name, tags or rollout status rather than listing every flag
4. Set HARNESS_READ_ONLY for analysis tasks; leave confirmation on for kill, restore and delete
5. On 429, wait at least the larger X-RateLimit-Reset-Seconds value before retrying

### Mostly Good Metrics

1. Use query_metrics for several aggregate questions instead of repeated execute_query calls
2. Pass inline definitions to execute_funnel and execute_retention rather than creating saved objects
3. Confirm with the user before delete, revoke_api_key or stop_experiment calls, since the server doesn't ask
4. Start a fresh agent session after connecting, since a running client may not reload the tool list
5. On 429 from ingestion, wait for Retry-After before resending events

## Questions

### Which is better for AI agents, Harness Feature Management & Experimentation or Mostly Good Metrics?

Harness Feature Management & Experimentation scores 69.2 (B) on agent readiness against Mostly Good Metrics's 41.7 (E), and leads in 6 of 7 scored categories. Mostly Good Metrics leads on payments & pricing.

### Do Harness Feature Management & Experimentation and Mostly Good Metrics need an API key?

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

### Can an agent call Harness Feature Management & Experimentation and Mostly Good Metrics without installing anything?

Yes. Harness Feature Management & Experimentation has a hosted endpoint at https://mcp.harness.io/mcp and Mostly Good Metrics at https://app.mostlygoodmetrics.com/mcp.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/harness-fme-vs-mostly-good-metrics.json, and with the fewest tokens: https://www.anchorterminal.com/compare/harness-fme-vs-mostly-good-metrics.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "harness-fme", "b": "mostly-good-metrics"}`. From a terminal: `anchor compare harness-fme mostly-good-metrics`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/harness-fme.json and https://www.anchorterminal.com/api/v1/tools/mostly-good-metrics.json

## Other comparisons with Harness Feature Management & Experimentation or Mostly Good Metrics

- [Amplitude vs Mostly Good Metrics](https://www.anchorterminal.com/compare/amplitude-vs-mostly-good-metrics.md)
- [Basedash MCP vs Mostly Good Metrics](https://www.anchorterminal.com/compare/basedash-mcp-vs-mostly-good-metrics.md)
- [Countly vs Mostly Good Metrics](https://www.anchorterminal.com/compare/countly-vs-mostly-good-metrics.md)
- [Fullstory vs Mostly Good Metrics](https://www.anchorterminal.com/compare/fullstory-vs-mostly-good-metrics.md)
- [Matomo vs Mostly Good Metrics](https://www.anchorterminal.com/compare/matomo-vs-mostly-good-metrics.md)
- [Mixpanel vs Mostly Good Metrics](https://www.anchorterminal.com/compare/mixpanel-vs-mostly-good-metrics.md)
- [Mostly Good Metrics vs OpenPanel](https://www.anchorterminal.com/compare/mostly-good-metrics-vs-openpanel.md)
- [Mostly Good Metrics vs Optimizely Experimentation](https://www.anchorterminal.com/compare/mostly-good-metrics-vs-optimizely.md)
- [Mostly Good Metrics vs Pendo](https://www.anchorterminal.com/compare/mostly-good-metrics-vs-pendo.md)
- [Mostly Good Metrics vs PostHog](https://www.anchorterminal.com/compare/mostly-good-metrics-vs-posthog.md)
- [Mostly Good Metrics vs Statsig](https://www.anchorterminal.com/compare/mostly-good-metrics-vs-statsig.md)
- [Mostly Good Metrics vs Userpilot](https://www.anchorterminal.com/compare/mostly-good-metrics-vs-userpilot.md)
- [Mostly Good Metrics vs Woopra](https://www.anchorterminal.com/compare/mostly-good-metrics-vs-woopra.md)
- [Amplitude vs Harness Feature Management & Experimentation](https://www.anchorterminal.com/compare/amplitude-vs-harness-fme.md)
- [Countly vs Harness Feature Management & Experimentation](https://www.anchorterminal.com/compare/countly-vs-harness-fme.md)
- [Flagsmith vs Harness Feature Management & Experimentation](https://www.anchorterminal.com/compare/flagsmith-vs-harness-fme.md)
- [Harness Feature Management & Experimentation vs LaunchDarkly](https://www.anchorterminal.com/compare/harness-fme-vs-launchdarkly.md)
- [Harness Feature Management & Experimentation vs Mixpanel](https://www.anchorterminal.com/compare/harness-fme-vs-mixpanel.md)
- [Harness Feature Management & Experimentation vs Optimizely Experimentation](https://www.anchorterminal.com/compare/harness-fme-vs-optimizely.md)
- [Harness Feature Management & Experimentation vs PostHog](https://www.anchorterminal.com/compare/harness-fme-vs-posthog.md)
- [Harness Feature Management & Experimentation vs Statsig](https://www.anchorterminal.com/compare/harness-fme-vs-statsig.md)
- [Fullstory vs Harness Feature Management & Experimentation](https://www.anchorterminal.com/compare/fullstory-vs-harness-fme.md)
- [Harness Feature Management & Experimentation vs Heap](https://www.anchorterminal.com/compare/harness-fme-vs-heap.md)
- [Harness Feature Management & Experimentation vs OpenPanel](https://www.anchorterminal.com/compare/harness-fme-vs-openpanel.md)
- [Harness Feature Management & Experimentation vs Woopra](https://www.anchorterminal.com/compare/harness-fme-vs-woopra.md)
- [Heap vs Mostly Good Metrics](https://www.anchorterminal.com/compare/heap-vs-mostly-good-metrics.md)
- [Flagsmith vs Mostly Good Metrics](https://www.anchorterminal.com/compare/flagsmith-vs-mostly-good-metrics.md)
- [GrowthBook vs Harness Feature Management & Experimentation](https://www.anchorterminal.com/compare/growthbook-vs-harness-fme.md)
- [GrowthBook vs Mostly Good Metrics](https://www.anchorterminal.com/compare/growthbook-vs-mostly-good-metrics.md)
- [Harness Feature Management & Experimentation vs Matomo](https://www.anchorterminal.com/compare/harness-fme-vs-matomo.md)
- [LaunchDarkly vs Mostly Good Metrics](https://www.anchorterminal.com/compare/launchdarkly-vs-mostly-good-metrics.md)

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Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp