Leviathan

codebase-memory-mcp is an MCP server from DeusData that indexes a codebase into a persistent local knowledge graph for AI coding agents. It parses source with tree-sitter AST grammars and uses Hybrid LSP semantic type resolution for selected languages to model functions, classes, call chains, HTTP routes, and cross-service links. Its MCP tools support code search, structural and Cypher-style queries, call tracing, architecture overviews, impact analysis, dead-code detection, and graph visualization. The project is distributed as native executables for macOS, Linux, and Windows, with no language runtime, hosted service, or API key required. Processing is local; the repository describes a RAM-first pipeline using compressed data, in-memory SQLite, and fused Aho-Corasick pattern matching, and reports sub-millisecond structural queries. A local visualization interface is available at localhost:9749.

deja-vu is a local memory and search layer for AI coding agents. Its Go binary indexes session histories already stored on a machine by Claude Code, Codex, Cursor, and other supported agents, including sessions recorded before installation, without using an LLM or embeddings. It provides natural-language and direct search, session inspection, context retrieval, JSON output, redaction, usage statistics, and MCP-based cross-agent recall; the index strips keys and tokens as it is built and can synchronize append-only memory between machines over SSH. Recall can be injected automatically at session start and before prompts, file edits, or commands, and a post-command hook can retrieve what followed a matching failure when the agent supports those hooks. It also indexes files opened during each turn, executed commands and exit statuses, and exact spans replaced by edits, rather than only conversation text. Decisions can be marked as accepted or rejected with notes, and results can report when indexed files have changed since a session. The repository reports sub-millisecond lookups over 5 GB of history, with benchmark harnesses for LongMemEval-S and LoCoMo. The project is distributed as a local binary with installation options including a shell script, Homebrew, Go, npm, Scoop, release archives, and agent-specific plugin or MCP bundles. Its optional installation wiring configures supported agents for MCP and session-start recall.

Claude-Mem is an open-source persistent-memory plugin and service for coding agents. It captures agent activity through lifecycle hooks, stores sessions, observations, and summaries in SQLite, and uses hybrid full-text and Chroma vector search to retrieve relevant context across sessions. Its MCP search workflow uses progressive disclosure: the agent first searches a compact index, then reviews a timeline, and finally fetches full observations for selected result IDs. A local worker service, managed by Bun, provides the HTTP API, search endpoints, and web viewer; the project also supports integrations with Claude Code and other listed agent environments, configurable context injection, private-content exclusion tags, and optional cloud synchronization. The repository states that it is distributed under the Apache License 2.0 and requires Node.js 20 or later, with Bun, uv, and SQLite used by the runtime. It can be installed through its npx installer or Claude Code's plugin marketplace.

Context Mode is an MCP server and plugin for AI coding agents that reduces context-window usage by routing large tool outputs through sandboxed subprocesses. Its execution tools run code in supported languages, process files, fetch and analyze URLs, and return selected stdout or search results instead of exposing raw logs, snapshots, API responses, or file contents to the conversation. The project reports up to 98% context reduction in its benchmarks. It also provides session continuity across supported agents. Hooks capture tool calls, edits, prompts, decisions, errors, and other session events in SQLite; before compaction, the system builds a prioritized resume snapshot, and after compaction or session resumption it retrieves relevant events through SQLite FTS5 search with BM25 ranking. Content indexing uses heading-aware chunking, stemming, trigram matching, reciprocal-rank fusion, proximity reranking, fuzzy correction, and smart snippets. The MCP interface includes execution, batching, indexing, search, fetching, statistics, diagnostics, upgrade, and purge tools. Context Mode supports multiple coding-agent platforms through MCP servers, native plugins, and platform-specific hooks, with automatic routing enforcement where hooks are available and instruction files for platforms without them. The repository states that processing and SQLite storage are local, with no account or telemetry requirement. It is licensed under the Elastic License 2.0, which permits use, modification, and distribution but restricts offering the software as a hosted or managed service and removing licensing notices.

MCP-Memory is a Model Context Protocol server that gives AI coding agents persistent memory across chat turns and sessions. It stores memory records as human-readable Markdown documents following the Open Knowledge Format (OKF v0.2), with YAML frontmatter, hierarchical index files, and an update log, while maintaining a local SQLite FTS5 index for key lookups, keyword search, tag filtering, and namespace-scoped retrieval. The server exposes MCP tools for storing, retrieving, searching, and deleting memories, and supports project, user, and default namespaces; a setup wizard configures supported MCP clients including Claude Desktop, Cursor, Antigravity, Windsurf, and Codex.