Hypertune MCP by usefulapi

Server Details

Evaluate and inspect your Hypertune feature flags from your AI assistant.

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Status: Healthy
Uptime: 68.5% over 54 days
Last Tested: 2026-10-10 18:54
Transport: Streamable HTTP · MCP 2025-06-18
URL
Repository: m190/usefulapi-mcp
GitHub Stars: 0

TDQS

A4.3/5.0

Scored 2026-08-31 12:46 across 5 tools

Disambiguation4/5

Evaluate and get_logic are clearly distinct (resolved values vs raw logic), and query is positioned as an escape hatch. The only mild overlap is introspect and list_flags, both derived from introspection, though descriptions distinguish broad schema discovery from a flag-focused convenience list.

Naming Consistency4/5

All tools share the hypertune_ prefix and use snake_case, which gives a predictable base. The right-hand side mixes bare verbs like evaluate and query with verb-noun pairs like get_logic and list_flags, so naming is mostly consistent but not perfectly uniform.

Tool Count5/5

Five tools is a tight, focused set for a feature-flag evaluation and introspection server. Each tool serves a clear purpose and the count feels neither thin nor bloated.

Completeness4/5

The set covers the core workflows: discover schema, list flags, inspect logic, evaluate flags, and run arbitrary queries. It omits flag management mutations, but the tool descriptions suggest a query-oriented scope rather than full CRUD, so this is a minor gap at most.

Available Tools

5 tools

hypertune_evaluateEvaluate feature flags

Read-only

Inspect

Evaluate one or more feature flags for a given context and get their resolved values. Builds query { root(context: <context>) { <selection> } }. Provide selection = the flag fields to read (e.g. exampleFlag anotherFlag { nestedField }) and context = the evaluation context (environment + user/attributes). Every field must supply all of its arguments (Hypertune reduces the flag logic to a JSON result). Use hypertune_list_flags / hypertune_introspect first if you don't know the flag names.

ParametersJSON Schema

Name	Required	Description	Default
`context`	No	Evaluation context object, inlined as the `context` arg. e.g. {"environment":"production","user":{"id":"u_123","email":"a@b.com"}}. Omit to return the flag LOGIC instead of a reduced value.
`selection`	Yes	GraphQL selection of flag fields under root, e.g. `exampleFlag` or `homePage { showBanner } exampleFlag`.

hypertune_get_logicGet flag logic (unreduced)

Read-only

Inspect

Fetch the underlying LOGIC of flags without reducing them — i.e. query { root { <selection> } } with no context. Returns the flag's conditional expression / rules rather than a single resolved value, useful for inspecting how a flag is configured. If the schema requires a context arg you can still pass a partial one via context.

ParametersJSON Schema

Name	Required	Description	Default
`context`	No	Optional partial context, inlined as the `context` arg if the schema requires it.
`selection`	Yes	GraphQL selection of flag fields under root, e.g. `exampleFlag`.

hypertune_introspectIntrospect the GraphQL schema

Read-only

Inspect

Run a GraphQL introspection query to discover the project's schema — all types and fields, including the available flags and the shape of the evaluation context. Best-effort: some edge deployments disable introspection, in which case this returns a clear error (use hypertune_query with a known flag name instead).

ParametersJSON Schema

Name	Required	Description	Default
No parameters

hypertune_list_flagsList feature flags

Read-only

Inspect

List the project's top-level feature flags (the fields of the query root type) with their return types and descriptions, derived from GraphQL introspection. A convenient first call to see what flags exist before evaluating. Requires introspection to be enabled on the edge endpoint.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

hypertune_queryRun a raw GraphQL query

Read-only

Inspect

Run an arbitrary GraphQL query (and optional variables) against the Hypertune edge endpoint. Power-user escape hatch for full control — each Hypertune project has its own generated schema, so this handles any flag shape, nested selections, inline enum literals, or variables the convenience tools can't express. The query root field is root(context: ...).

ParametersJSON Schema

Name	Required	Description	Default
`query`	Yes	A complete GraphQL query string, e.g. `query { root(context: {environment: "production"}) { myFlag } }`.
`variables`	No	Optional GraphQL variables object matching the query's declared variables.