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Glama

Server Details

Deterministic fitness coaching engine: adaptive programs, progression math, readiness autoregulation

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

Glama MCP Gateway

Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.

MCP client
Glama
MCP server

Full call logging

Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.

Tool access control

Enable or disable individual tools per connector, so you decide what your agents can and cannot do.

Managed credentials

Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.

Usage analytics

See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.

100% free. Your data is private.
Tool DescriptionsA

Average 3.8/5 across 10 of 10 tools scored. Lowest: 3.2/5.

Server CoherenceA
Disambiguation5/5

Each tool has a clearly distinct purpose: changelog explains coaching decisions, get_program provides the full program, get_todays_session shows the immediate workout, list_swap_options and swap_exercise handle exercise substitution, log_workout records lifts, meal_plan and nutrition_targets cover nutrition, readiness_checkin handles daily readiness, and regenerate_program rebuilds the program. There is no ambiguity or overlap.

Naming Consistency4/5

Most tools follow a verb_noun pattern (get_program, list_swap_options, log_workout, regenerate_program, swap_exercise). Two tools (changelog, meal_plan, nutrition_targets) are noun-only, which is a minor inconsistency but does not cause confusion. Overall, the naming is clear and predictable.

Tool Count5/5

With 10 tools covering program viewing, daily sessions, exercise swapping, workout logging, nutrition, readiness, and program regeneration, the count is well-scoped for a fitness coaching engine. Each tool serves a clear need without redundancy.

Completeness3/5

The tool set covers core workflows: program management, workout execution, exercise swapping, nutrition, and readiness. However, there is no tool to update athlete profile data (e.g., body stats, goals), which is needed for regeneration based on profile changes. This is a notable gap that could cause agent failures.

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