Infer MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| INFER_MCP_CONFIG | No | JSON string containing configuration | |
| INFER_MCP_CONFIG_PATH | No | Path to JSON configuration file |
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| sshExecuteB | Execute a command on a remote server via SSH using a configured profile |
| dbQueryB | Execute a SQL query on a PostgreSQL database using a configured profile |
| trainClassifierB | Run classifier training commands on a remote host via SSH |
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 3 tools
Each tool has a clearly distinct purpose: dbQuery handles SQL queries on PostgreSQL, sshExecute runs general commands via SSH, and trainClassifier specifically trains classifiers via SSH. There is no overlap in functionality, making tool selection unambiguous for an agent.
The naming is mixed: dbQuery and sshExecute follow a verb_noun pattern, but trainClassifier uses a verb_noun format without underscore separation. While readable, this inconsistency in convention (snake_case vs. camelCase) reduces predictability across the set.
With only 3 tools, the server feels thin for a general-purpose 'Infer MCP Server' that spans database queries, SSH execution, and machine learning tasks. This limited set may not adequately cover the implied scope, leaving gaps in related operations.
The tool surface is severely incomplete for the inferred domain of data and remote operations. There are no tools for database management (e.g., create/update tables), SSH file operations, or classifier evaluation/deployment, creating significant gaps that will hinder agent workflows.