fja-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| evaluate_outputC | Evaluate an LLM response using FJA criteria. |
| compare_outputsC | Compare two candidate responses and recommend the one more aligned with FJA. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| fja_review_prompt | Provide an FJA-aligned review prompt template. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| fja_principles | Return a human-readable description of the FJA principles. |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one evaluates a single response, the other compares two responses. There is no overlap in functionality, and an agent can easily select the appropriate tool based on whether it needs a single evaluation or a comparison.
Both tool names follow a consistent verb_noun pattern: evaluate_output and compare_outputs. The naming is predictable and aligns with their functions, making it easy to infer behavior from the name.
With only two tools, the server feels minimal but covers the core evaluation and comparison tasks. However, it is on the thin side for a dedicated server, and additional tools like batch evaluation or criteria management could round it out.
The server provides essential single and comparative evaluation capabilities, which are the primary use cases. Minor gaps exist, such as lacking a tool to retrieve or modify FJA criteria, but these are not critical for basic evaluation workflows.