Enterprise Code Search MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| BATCH_SIZE | No | Batch size for indexing | |
| CHROMA_HOST | No | The host for ChromaDB | |
| CHROMA_PORT | No | The port for ChromaDB | |
| OLLAMA_HOST | No | The host URL for Ollama service | |
| COMPANY_NAME | No | Your company name | |
| OLLAMA_MODEL | No | The Ollama model to use for embeddings | |
| OPENAI_MODEL | No | The OpenAI model to use for embeddings | |
| MAX_FILE_SIZE | No | Maximum file size in KB | |
| MAX_CHUNK_SIZE | No | Maximum chunk size in characters | |
| OPENAI_API_KEY | No | Your OpenAI API key | |
| CHROMA_SERVER_HOST | No | ChromaDB server host for restricting access | |
| EMBEDDING_PROVIDER | No | The embedding provider to use (ollama or openai) |
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 |
|---|---|
| index_local_projectC | Index a local project directory into the vector database |
| search_codebaseC | Search the indexed codebase using semantic search |
| list_indexed_projectsB | List all projects currently indexed |
| get_embedding_provider_infoB | Get information about the current embedding provider |
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 4 tools
Each tool has a clearly distinct purpose with no overlap: get_embedding_provider_info retrieves configuration details, index_local_project handles indexing, list_indexed_projects enumerates existing projects, and search_codebase performs semantic queries. The descriptions clearly differentiate between setup, management, and query operations.
All tools follow a consistent verb_noun naming pattern (e.g., get_embedding_provider_info, index_local_project, list_indexed_projects, search_codebase). The verbs (get, index, list, search) are appropriately descriptive and maintain a uniform snake_case style throughout.
With 4 tools, this server is well-scoped for enterprise code search, covering essential operations: provider info retrieval, indexing, project listing, and semantic search. Each tool earns its place without redundancy, making the set manageable and focused on core functionality.
The toolset covers the primary workflows for code search: setup (get provider info), ingestion (index projects), management (list projects), and querying (search). A minor gap exists in update/delete operations for indexed projects (e.g., reindexing or removal), but agents can likely work around this with the provided tools.