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Provides code context, memory, search, and AI tooling for developers.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "ContextStream MCP Server" MCP server from askskill: Run: claude mcp add 'io-github-contextstreamio-mcp-server' -- npx -y @contextstream/mcp-server
Using the current project code, retrieve context related to the user login flow and list the key files, functions, and their relationships.
A summarized code context for the login flow, including relevant files, functions, and how they connect.
Search the project for all implementations related to caching and group them by module with a short purpose note.
A grouped list of cache-related code results with their locations and purposes.
Using existing memory, summarize the core components previously examined in this repository and point out areas that may need further review.
An overview of key components based on stored memory, plus suggested code areas for further inspection.
Developers can use it to retrieve code context and search relevant implementations in complex projects, reducing manual file hunting. It is useful for quickly understanding entry points, call relationships, and key modules.
When analyzing the same repository across multiple rounds, its memory capability can preserve previously reviewed information and help continue the investigation. This is useful for ongoing debugging or gradually learning a system’s structure.
When AI needs to better understand a project’s code, this MCP server can provide code context, search results, and related tooling. That helps improve the quality of answers grounded in the actual project content.
It is a ContextStream MCP Server that provides code context, memory, search, and AI tool capabilities. It is mainly aimed at code understanding and analysis workflows.
The provided information does not specify the runtime, keys, or external dependencies required. For exact prerequisites, see the source repository.
The current materials do not include installation or integration steps. Please see the source repository for details.
Give AI coding assistants persistent, structured project memory stored as local Markdown.
Give Claude Code persistent memory and semantic context retrieval across sessions.
Search repositories semantically and turn codebases into AI-ready context and knowledge.
Build semantic memory and structural code indexes for persistent AI project context.
Give AI coding agents long-term memory, search, and organization across sessions.
Give LLMs persistent semantic memory and vector search for better context continuity.