"Information on memory banks or task managers" matching MCP servers:

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

Long-term memory for AI coding agents, stored as a tree of plain local files. Agents search it before answering and save what lasts; changed facts are kept as history and flagged as outdated.

A stateless MCP server that gives coding agents a curated entry point to shared memory, orchestrating Hindsight (facts) and LightRAG (corpora) for automatic routing, URL ingestion, and consistency tooling.

Provides a memory server for coding agents over MCP, capturing and retrieving the meaning and rationale behind code decisions down to the function level. It enables agents to search product memory, get task context, and propose new memories to avoid re-deriving or re-breaking past decisions.

Enables AI coding agents to query a fully local SQLite FTS5 memory index of a codebase, returning high-density identity cards with exact line references, AST symbol contracts, phase maps, and colloquial intent search so agents can work without scanning raw files. It also supports incrementally syncing code changes and enriching knowledge under a six-pillar quality gate, keeping everything on-device with no cloud leakage.

Provides AI coding agents with a hybrid cognitive memory engine that reduces token usage, prevents amnesia, detects repetitive error loops, and retrieves relevant code context through MCP.

An MCP server that enables persistent memory, structured thinking sessions, and project-based knowledge management for Claude. It includes specialized coding tools for package discovery and reinvention prevention by validating code against existing libraries and APIs.

MCP server for local codebase memory: semantic indexing, hybrid search, and clean code analysis (static + LLM) with retrievable project notes, designed to run fully local on modest hardware.

Provides AI agents with causal code memory by indexing repositories into a graph of symbols and edges, enabling context-aware retrieval of relevant code slices.

A persistent memory MCP server for Claude Code that enables long-term recall across sessions via hybrid search, code intelligence, and tools for reading/writing memory.

It enables AI coding agents to store and retrieve persistent conversational and project memory, search code by behavior, rank likely bug candidates, and enforce ambient lifecycle hooks.

Provides long-term memory and codebase AST intelligence for AI coding agents, enabling persistent context handoff and high-efficiency symbol queries.

Enables coding agents to perform read-only source investigation via a local SQLite index, offering status, search, backlog, context, impact, and drift tools for TypeScript, JavaScript, and Java codebases.

A local semantic memory and code-indexer that uses AST parsing for structural understanding and persists architectural decisions to help AI assistants bypass context window limits.

MCP server for semantic code indexing using vector embeddings, enabling AI agents to maintain persistent memory of codebases through natural language queries and intelligent chunking.

TMF helps AI coding agents detect stale source context and retrieve source-linked code understanding on demand. It preserves traceable context across code paths so agents can consider upstream and downstream effects when making changes.

Enhances Claude AI with persistent memory storage for Infrastructure-as-Code components, supporting version tracking and relationship mapping for Terraform and Ansible resources.

High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 159 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

A Docker-based MCP server providing codebase memory and search tools. It enables storing/retrieving memories, regex search of code, and file summarization for AI assistants.

Serves semantic fact memory and a code knowledge graph from a single process, enabling agents to store facts pinned to the symbols they describe and to recall answers together with the relevant code. It also supports project-scoped facts, TTL-based staleness checks, reverse lookup of facts for a symbol, and impact/trace analysis across linked symbols.

MCP server that wraps codebase-memory-mcp to provide code indexing, search, tracing, and architecture analysis tools with automatic reindexing after source changes.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

Enables deterministic behavioral regression review of pull-request diffs by checking changed code against approved incident-derived contracts. It exposes read-only tools to assess diffs and pull requests, list and fetch contracts, and report outcomes over stdio without mutating repositories.

Enables structural knowledge-graph code search, AST snippet retrieval, architecture analysis, call-path tracing, and textual code search across indexed repositories, plus an auto-started graph visualization UI.

Local repository memory for Codex that indexes TypeScript/JavaScript structure into local SQLite, exposes compact MCP tools, and renders deterministic SVG/map frames.

Provides persistent memory and semantic code understanding for AI assistants using MongoDB Atlas Vector Search. Enables intelligent code search, memory management, and pattern detection across codebases with complete semantic context preservation.

Local-first MCP-style code memory for research repositories: enables file search, Python symbol extraction, import graph, and repo context packs.

Provides a dynamic SQLite-backed code knowledge graph for AI assistants, with MCP tools to inspect symbols, find dependency paths, and analyze code structure across multiple languages.

A non-invasive MCP bridge that makes DevSpace search tools memory-aware by augmenting search/list tool responses with codebase memory context.

A local-first MCP server that gives AI coding agents durable project memory, dependency graphs, and impact analysis to answer team knowledge and cross-file change questions before editing.

Local memory for coding agents that can refuse, not only recall. A rule carrying a machine-checkable proof blocks the matching command before it runs, while prose-only rules can warn but never block.

Local-first repository memory for AI coding agents that indexes codebases into SQLite and exposes it through MCP tools, with a browser dashboard for architecture inspection.

Enables remote MCP clients to list indexed projects, search and traverse a code graph, and trigger indexing over an authenticated Streamable HTTP endpoint on a private tailnet, while destructive tools are hard-refused and every call is audited.

Enables AI assistants to maintain persistent understanding of code projects across chat sessions via a SQLite brain that caches structural maps, summaries, and decisions. Provides tools for querying project structure, searching code, and recording insights to reduce token usage and avoid re-analysis.

MCP server that indexes TypeScript/React project symbols in memory, enabling agents to find definitions, references, and dependencies without reading the whole repo. Also includes a local visual dashboard with no outbound network calls.

Provides local-first project memory and compact engineering context for Codex and DeepSeek Harness, enabling agents to persist and retrieve project-scoped decisions, task checkpoints, and deterministic EIR/1 engineering facts across sessions.

Enables coding agents to explore TypeScript, JavaScript, and Prisma projects through local symbol, call, and model-usage graphs, while recalling persistent project-scoped decisions and returning focused source context.

Enables local semantic code search across repositories using natural language, with AST-aware chunking and hybrid vector/FTS5 retrieval.

An AI debugging agent MCP server that enables autonomous plan-act-observe debugging workflows, allowing repository exploration, code inspection, human-approved edits, and test execution through structured MCP tools.

Allows Claude Code to request an independent code review from Google Antigravity (Gemini, Claude, or GPT-OSS) via the Antigravity CLI, providing a second opinion on plans or diffs.