"Aufgaben von Claude zu Gemini zuweisen, um Token zu sparen" matching MCP servers:

Provides structured local memory for Claude Desktop, reducing token usage by over 95% through intelligent retrieval and layered storage.

A remote MCP server that compresses long text contexts, stores compact reusable summaries, and retrieves relevant context by title/tag/query, helping reduce token usage.

Pull Deep Memory from across your Claude Code Sessions — when you need it.

Persistent project context for Google Gemini. 12 MCP tools for .faf Project DNA — auto-detect your stack, validate, score, and sync across CLAUDE.md, GEMINI.md, and AGENTS.md. Python/FastMCP. IANA-registered format (application/vnd.faf+yaml). 183 tests. One file, every AI platform.

A persistent semantic memory system for Claude Code that provides a structured, versioned document store with semantic search and graph visualization. It acts as a memoization layer to store and retrieve research, design decisions, and codebase insights across different work sessions.

Self-improving learning engine for Claude Code. Extracts signals from sessions (corrections, successes,confusion), runs periodic reflections, and evolves behavioral frameworks through evidence. 9 MCP tools, automatichooks, local-only.

Overcomes Claude Code's 200k token context limit by implementing persistent long-term memory using Redis and AI-powered state summarization. Enables seamless checkpoint and resume of project context across sessions.

An MCP server that gives Claude persistent, locally-stored memory with verification-gated lessons and a Pattern Oracle to prevent unverified guesses from becoming ingrained facts.

Post-hoc session handoff and project memory for Claude Code: MCP tools list_sessions and handoff turn any session — even crashed or usage-limit-hit ones — into a clean handoff.md another model can continue from, with secrets redacted from every output. Zero dependencies, fully local; also distills a project's entire session history into one cited memory brief.

Enables creation and querying of knowledge bases using Google's Gemini API File Search feature, allowing AI applications to upload documents and retrieve information through RAG (Retrieval-Augmented Generation).

MCP server that lets you search your Claude Code conversation history to find past solutions, track file changes, and learn from previous work.

Persistent memory and session intelligence for AI coding assistants. Auto-tracks mistakes, decisions, and context via hooks. Mines your full session history for patterns, predictions, and cross-session search.

Provides owner-bound secure storage and retrieval of tool outputs via MCP tools, enabling trusted persistence for agents like Claude Code, Codex CLI, and OpenCode.

Provides persistent, searchable memory for Claude Code using local SQLite, semantic embeddings, and full-text search, enabling Claude to recall and retrieve context across sessions and projects without external services.

An MCP server that enables Claude to search, retrieve, and contribute to a community-driven archive of AI-generated solutions, notes, skills, and tools, fostering knowledge sharing among AI agents.

A lightweight journal/memory system for Claude Code with no ML dependencies, using SQLite for fast local storage.

Local-first MCP server that enables multiple Claude agents to coordinate through a shared message bus with SQLite persistence and real-time clock anchoring.

Enables Claude Code to search and retrieve information from its past session transcripts, including tool calls, errors, and project-specific history, via an SQLite FTS5 full-text search index.

Gives Claude durable, queryable memory by logging every prompt/response to Supabase Postgres and exposing MCP tools to save, search, and retrieve conversation history.

A lightweight MCP server that gives Claude Code Channels on Telegram persistent memory by storing facts, conversation logs, and session summaries in Supabase.