"Information About Persistent Memory" matching MCP servers:

Provides coding agents with persistent, evidence-backed project memory and knowledge across sessions, using a structured memory tree and local knowledge base.

Gives AI coding assistants persistent memory, safety controls, and project awareness by tracking coding sessions, protecting critical files from modifications, and managing approval workflows with automatic changelog generation.

Persistent, local memory for AI coding agents that learns how you work, not just what you said. Supports Claude Code, Codex CLI, Cursor, and any MCP client.

Persistent memory for AI coding agents

Provides persistent memory for AI coding agents through the Model Context Protocol, enabling them to store and retrieve project knowledge across sessions.

Provides persistent long-term memory for AI coding agents by storing entities, relations, and observations across different sessions. It enables users to manage and query structured knowledge like coding preferences, project patterns, and technical solutions via a graph-based storage system.

On-device memory system for AI coding agents that captures commands, edits, and test results in a lossless ledger plus distilled facts, then provides selective recall over MCP with tools like remember, recall, search, and ask.

Provides repository-scoped safe memory for AI coding agents with just-in-time verification against file changes to ensure facts remain accurate. It links memories to specific code citations and automatically marks them as stale if the underlying source code is modified or deleted.

Provides a file-based, git-friendly memory store for coding agents to persist and recall project-specific lessons, bugs, and conventions via JSON files in the repository.

A graph-based MCP server that provides AI coding agents with persistent memory to store patterns, track complex relationships, and retrieve knowledge across sessions. It leverages graph structures to handle temporal queries and relational paths that traditional vector stores often miss.

An in-memory knowledge graph MCP server that gives coding agents structural and semantic recall over codebases by indexing Python source, ADR documents, and project configuration, exposing 7 tools for search, traversal, context retrieval, and natural-language Q&A.

A 68-tool MCP server providing persistent memory, error tracking, decision logging, task orchestration, and multi-modal AI generation for coding agents like OpenCode and Claude Code.

Enables AI clients to send prompts to a local Codex App Server via MCP, returning text responses and supporting persistent session reuse.

Scoped, low-latency persistent memory layer for AI agents, Cursor, and Claude Code over Model Context Protocol with sub-50ms hybrid search.

Provides a persistent memory and governance layer that allows AI coding agents to query documented architecture rules and validate code against team standards. It enables agents to verify compliance across categories like security and testing before suggesting changes to ensure consistency across development sessions.

Provides MCP tools to create, run commands in, checkpoint, and delete durable cloud environments, giving coding agents persistent state between calls.

Shared, code-grounded memory for developers and their coding agents. Capture a learning once and the whole team plus every agent recalls it; memory is grounded in your code and stored as git-tracked JSON reviewed in PRs, with citations validated on write and stale memory withheld from recall. Works with any MCP client.

Provides a secure interface to run Anthropic's Claude Code CLI as an MCP server, enabling task execution, persistent memory, and integration with MCP-enabled IDEs.

Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.

Enables AI agents to execute Python, TypeScript, and JavaScript code in persistent Jupyter kernels with stateful variables and imports across interactions.