Skip to main content
Glama
ozwei

LM Studio MCP Bridge

by ozwei

query_local_file

Reads a local file and queries a local LLM about its contents, enabling private, on-device Q&A.

Instructions

Privacy-First: Reads a local file and queries the local LLM about its contents.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesYour question about the file.
file_pathYesAbsolute path to the file.
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the burden. It mentions 'Privacy-First' implying local-only processing, but doesn't disclose behavioral details such as file access requirements, return format, or potential side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence, which is concise and front-loaded with the key purpose. No wasted words, though it's minimal.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and minimal annotations, the description is insufficiently complete. It doesn't explain what the response looks like, how the file is processed, or any caveats about local LLM querying.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and both parameters have clear descriptions in the schema. The tool description adds no additional parameter semantics beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: reads a local file and queries the local LLM about its contents. It differentiates from siblings like read_file_content and query_local_llm by combining both actions, but doesn't explicitly name alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives like read_file_content or query_local_llm. The 'Privacy-First' tag hints at local processing but doesn't provide clear usage context or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ozwei/lmstudio-mcp-bridge'

If you have feedback or need assistance with the MCP directory API, please join our Discord server