C

Chroma MCP

Chroma is an open-source vector database that provides memory support for Python and JavaScript LLM applications, supporting multiple client types and document operations.
3 points
675

What is the MCP Server?

The MCP server is an open-source tool built on Chroma that enhances the capabilities of LLMs (Large Language Models) by providing context data to AI models. It supports multiple data retrieval methods, such as vector search, full-text search, and metadata filtering.

How to Use the MCP Server?

You can start using the MCP server in just a few simple steps. First, install the necessary dependencies. Then, choose the appropriate client type according to your needs (such as cloud client, HTTP client, or local client). Finally, configure the connection and run queries.

Application Scenarios

The MCP server is well-suited for application scenarios that require enhanced LLM memory capabilities, such as chatbots, knowledge base management, and personalized recommendation systems.

Main Features

Flexible Client TypesSupports multiple client types, including cloud clients, HTTP clients, persistent clients, and temporary clients.
Powerful Data Manipulation CapabilitiesSupports creating, modifying, and deleting collections, as well as advanced data querying and filtering functions.
Embedding Function SupportComes with multiple built-in embedding functions, such as default, Cohere, OpenAI, etc., for easy and quick integration.

Advantages and Limitations

Advantages
Open source and free to use
Supports multiple embedding functions and query methods
Easy to integrate into existing systems
Limitations
Performance may be limited for large-scale datasets
Requires a certain technical background for efficient configuration

How to Use

Install the MCP Server
Download and install the MCP server and its dependencies.
Configure the Client
Choose the client type according to your needs and configure the connection parameters.
Run Queries
Execute queries to obtain the desired results.

Usage Examples

Example 1: Add Documents to a CollectionAdd documents to a collection and perform queries.
Example 2: Query DocumentsRetrieve documents based on query conditions.

Frequently Asked Questions

How to choose the appropriate client type?
Does it support custom embedding functions?

Related Resources

Official Documentation
Detailed usage guides and technical documentation.
GitHub Repository
The project's source code and contribution guidelines.
Installation
Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.
A
Apple Notes MCP
A server that provides local Apple Notes database access for the Claude desktop client, supporting reading and searching of note content.
Python
201
4.3 points
M
MCP Alchemy
Certified
MCP Alchemy is a tool that connects Claude Desktop to multiple databases, supporting SQL queries, database structure analysis, and data report generation.
Python
317
4.2 points
P
Postgresql MCP
A PostgreSQL database MCP service based on the FastMCP library, providing CRUD operations, schema inspection, and custom SQL query functions for specified tables.
Python
105
4 points
A
Awesome MCP List
This is a continuously updated curated list of MCP servers, covering multiple categories such as browser control, art and culture, cloud platforms, command - line, communication, customer data platforms, databases, developer tools, data science tools, file systems, finance and fintech, games, knowledge and memory, location services, marketing, monitoring, search, and utilities. Each project comes with a GitHub link and the number of stars, making it easy for users to quickly understand and use.
703
5 points
W
Wren
Wren Engine is a semantic engine designed for MCP clients and AI agents, providing semantic layer support to enable AI to accurately understand enterprise data models and business logic. It supports multiple data sources and is embedded in MCP clients to ensure the accuracy and governance of data interaction.
Java
392
4 points
M
MCP Server Weread
The WeRead MCP Server is a lightweight service that bridges WeRead data and AI clients, enabling in - depth interaction between reading notes and AI.
TypeScript
371
4 points
M
MCP Redis
Certified
Redis MCP Server is a natural language interface service designed for Redis, supporting AI agents to query and manage Redis data through natural language, integrating the MCP protocol, and providing multiple data structures and search functions.
Python
74
4.5 points
M
MCP Obsidian
This project is an MCP server used to interact with the Obsidian note application through the Local REST API plugin of Obsidian. It provides various tools to operate and manage files in Obsidian, including listing files, retrieving file content, searching, modifying content, and deleting files.
Python
876
5 points
Featured MCP Services
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
1.7K
5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
823
4.3 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
79
4.3 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
130
4.5 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
554
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
6.6K
4.5 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
5.2K
4.7 points
M
Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
745
4.8 points
AIbase
Zhiqi Future, Your AI Solution Think Tank
© 2025AIbase