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An MCP server for persistent memory, knowledge bases, and project summaries.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "mcp-kb-server" yet — see the docs or source repo.
Save the key decisions, term definitions, and open tasks of the current project into the knowledge base, and prioritize them in future conversations.
The tool persistently stores project context for reuse in later conversations and tasks.
Using the existing memory and knowledge entries for the current project, generate a project summary covering goals, progress, risks, and next steps.
Outputs a structured project summary for quickly understanding the current status.
Detect which project I am currently working on and file the new information from this conversation under that project.
The tool automatically identifies the project and organizes new content into the corresponding project space.
Developers or product managers use it to preserve project context, decisions, and terminology across multiple sessions, avoiding repeated setup. It fits AI workflows that need long-term memory.
When team members need a fast overview of a project, they can use its project summary capability to compile goals, current status, and next actions. This helps them get up to speed faster.
When users need a unified view of project memory, knowledge base content, and summaries, they can manage them through the interactive dashboard. It is useful for people handling multiple project contexts.
It is an MCP server that provides persistent memory, a knowledge base, and project summary capabilities. The description also says it supports automatic project detection and an interactive dashboard.
Based on the provided description, yes. It explicitly mentions automatic project detection, but the exact detection method should be checked in the source repository.
The provided material does not include installation steps, runtime requirements, or key information. Please see the source repository for prerequisites and deployment details.
Manage project knowledge and requirements with fast full-text search and updates.
Secure internal knowledge retrieval with permission-aware access control and citation enforcement.
Centralize knowledge, run semantic search, ingest documents, and generate RAG answers.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.
Give AI agents persistent knowledge-graph memory and cross-session retrieval.
Give LLMs persistent, searchable access to project knowledge and session context.