LangChain & LlamaIndex Coding Assistant
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| SERPER_API_KEY | Yes | Your Serper API key for searching documentation (get one free at serper.dev) |
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 |
|---|---|
| get_docsA | Search the latest docs for a given query and library. Supports langchain, openai, and llama-index. Args: query: The query to search for (e.g. "Chroma DB") library: The library to search in (e.g. "langchain") Returns: Text from the docs |
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 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as searching documentation for specific libraries.
The single tool name 'get_docs' follows a clear verb_noun pattern. Since there is only one tool, naming consistency is inherently perfect with no deviations to assess.
A single tool is too few for a server labeled as a 'Coding Assistant' for LangChain and LlamaIndex. This scope suggests needs like code generation, debugging, or API interaction, which are not covered by just documentation search.
The tool surface is severely incomplete for the stated purpose. It only provides documentation search, missing essential operations like code execution, analysis, or integration with the libraries mentioned, leading to significant gaps in functionality.