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kanlanc

Lodestar MCP Server

by kanlanc
OverviewSchemaRelated ServersScoreDiscussions
Python

To start the project

uv venv
uv sync
mcp dev server.py

After every change in the code, you need to re run

mcp dev server.py

NOTE: You should look into how to do hot reloads

Look into how the other example mcp servers are running with their respective tool exposing

Potential next steps:

  • Should I expose API Keys and stuff as a resource or should i make the platform url as a resource

  • one of the tools should be getting a new api_key and project_id for the user if they dont have it for the current one but I need to get the right user somehow

  • Look into how the other tools are doing this stuff

Write mcp prompts that help llms understand how to write the prompts for best results

Servers to look at:

Looks lke most of these are using ts, maybe I should also change gears to that

Actually I dont see why typescript would be better especially in our usecase, so sticking to better readbility python might be better

Potential Contributions

Hot reload when the developer writes code to MCP

Available Tools

1 tool
doc_queryC

Query project documentation.

Args:
    query (str): The query text from the user
    api_key (str): Authentication key for the request
    project_id (str): Identifier for the target project
    
Returns:
    ContextResponse: The generated response
ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
api_keyYes
project_idYes

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions authentication via api_key and returns a ContextResponse, but fails to explain what the tool does beyond 'query' (e.g., how it processes queries, any rate limits, error handling, or what ContextResponse entails). This leaves significant gaps in understanding its behavior.

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 structured with clear sections for Args and Returns, making it easy to parse. It's front-loaded with the purpose statement and avoids unnecessary fluff. However, the parameter explanations are very brief and could be more informative without sacrificing conciseness.

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?

Given the complexity of a query tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the return value (ContextResponse is undefined), lacks details on query processing or limitations, and provides minimal parameter guidance, making it inadequate for full understanding.

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 0%, so the description must compensate. It lists all three parameters with brief explanations (e.g., 'query text from the user'), adding basic semantics beyond the schema's titles. However, it doesn't provide details like format constraints, examples, or deeper meaning, offering only minimal compensation for the lack of schema descriptions.

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

Purpose3/5

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

The description states the tool 'Query project documentation' which provides a clear verb ('Query') and resource ('project documentation'), establishing its basic purpose. However, it lacks specificity about what kind of querying it performs (e.g., semantic search, keyword matching, retrieval) and doesn't differentiate from siblings since there are none, making it somewhat vague.

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?

The description provides no guidance on when to use this tool, such as prerequisites, typical use cases, or alternatives. With no sibling tools, there's no need for differentiation, but it still lacks any context about appropriate scenarios or limitations, leaving usage unclear.

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

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TDQS

C2.9/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'doc_query' has a clearly defined purpose that cannot be confused with any other tool in the set.

Naming Consistency5/5

The single tool name 'doc_query' follows a clear verb_noun pattern. With only one tool, the naming is inherently consistent as there are no other tools to compare against or create inconsistencies with.

Tool Count2/5

A single tool feels thin for a documentation query server, suggesting limited functionality. While it might be appropriate for a minimal prototype, a production documentation server would typically offer multiple operations like search, browse, filter, or manage documentation, making this count borderline inadequate.

Completeness2/5

The tool surface is severely incomplete for a documentation domain. While 'doc_query' covers querying, there are obvious gaps: no tools for listing available documentation, managing documentation sets, filtering by categories, or handling documentation updates. This will likely cause agent failures when trying to perform comprehensive documentation tasks.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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