MCP LLM Integration Server
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
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| llm_predictC | Process text input through a local LLM |
| echoA | Echo back the input text for testing |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
llm_predict and echo are completely distinct in purpose—one performs LLM inference while the other is a simple testing utility. There is no overlap or ambiguity between them.
llm_predict uses a prefix-plus-verb compound while echo is a bare verb, showing mixed naming conventions. However, both names are short and readable, so the inconsistency is not chaotic.
With only two tools, the server sits at the borderline of feeling thin. For a minimal LLM integration demo the pair is acceptable, but a broader integration server would likely need more endpoints.
The server provides only one functional inference operation plus an echo test tool. Obvious gaps exist for an 'LLM integration server,' such as model management, parameter options, or alternative interaction modes like embeddings or chat.