"Vector Database" matching MCP servers:

Headless geometric memory engine for AI agents — no Vector DB, no cloud, no API key. Store and retrieve by meaning using native Vector Symbolic Architecture (NVSA) math over O_DIRECT NVMe mapping. Runs entirely on your machine via MCP.

Enables agents to track causal relationships, reconcile concurrent state changes, and coordinate consensus across distributed networks using vector clocks, CRDTs, gossip, and quorum-based protocols.

Provides MCP tools that give AI agents persistent, append-only memory in a git repository, letting them record observations, decisions, and corrections while retrieving context briefs, current facts, conflicts, and traceable event history without a vector database.

Enables AI agents to autonomously provision, pay for, and manage S3-compatible storage and vector databases without human intervention.

MCP server that enables AI agents to interact with Vector CANoe for automotive bus testing and diagnostics using natural language commands.

Free, deterministic, theory-traceable computational-creativity framework that generates, develops, contrasts, evaluates, and synthesizes structured creative ideas through MCP, with no accounts, database, or model inference.

A hybrid search MCP that enables users to find coding chunks like RAG without indexing their codebase, without any vector database. World's first context attention MCP. It gives results in below 5 seconds in a repository as big as VS Code.

Enables agents to stamp events with vector clocks, resolve state via LWW CRDT reconciliation, and coordinate distributed swarms through token-bucket gossip, Raft leader/quorum voting, and two-phase commit. It runs over MCP with zero external dependencies, delivering deterministic happens-before causal ordering and convergence across agent networks.

Pay-per-use semantic memory for AI agents with cryptographic attestation. Vector embeddings with SHA256 commitment, secp256k1 signature, and Lightning invoice.

Enables AI assistants to save and retrieve code snippets, generate language-specific style guides, create wiki documentation, and orchestrate multi-agent documentation workflows through MCP tools backed by vector search.

Slipstream - Built by Vektor Memory - a persistent multi-layered memory architecture. 4-layer associative graph memory (MAGMA) with autonomous REM cycle, CLI, DXT-MCP Cloak Tools.

A conversational application server that integrates LLM capabilities via Ollama with vector memory context, supporting multiple users, sessions, automatic history summarization, and a plugin system for executing real actions.

Provides AI assistants with long-term semantic memory capabilities through local vector-based storage. Enables storing, recalling, and managing information across sessions with complete privacy using ChromaDB, with no data ever leaving your machine.

Hand a human a rich interactive UI by URL from any MCP client and get structured data back: forms, approvals, surveys, pickers, editable lists. Round-trip human-in-the-loop for agents.

Enables external AI assistants and MCP clients to programmatically control Adobe Illustrator via WebSocket, supporting generative vector creation, layer organization, and document automation from natural language prompts.

Coordination for parallel coding agents: TTL file claims stored in the git common dir (visible across all worktrees), enforcement hooks that block colliding edits, agent presence, handoff notes, and a git-committed lessons knowledge base with BM25 search. Single static Go binary — no server, no database.

Enables multiple AI coding-agent sessions on one machine to hand tasks to each other and get results back through a shared local folder of JSON messages, with no cloud, database, or network service. Supports direct messages, broadcasts, blocking receive, and an optional headless worker that picks up, runs, and auto-replies to tasks.

A Model Context Protocol (MCP) server that provides intelligent search capabilities for discovering relevant Claude Agent Skills using vector embeddings and semantic similarity. This server implements the same progressive disclosure architecture that Anthropic describes in their Agent Skills enginee

A persistent, project-scoped memory layer for AI agents, supporting hybrid retrieval (vector, keyword, and tag matching) and sharing across different MCP clients like Claude Code, Qoder, or Cursor.

It gives AI agents a ranked, token-budgeted digest of what changed since their last cursor, with drill-down handles and cursor acknowledgement, read from a local database of file and SQL source changes. It enables agents to act on current business state without re-reading and diffing everything themselves.

Enables two coding agents to exchange tasks, results and bounded goal-driven conversations through a shared local SQLite database over MCP stdio, with atomic claims, expiring leases and optional headless dispatch. It keeps everything local, using no network service and payload-safe diagnostics.

I gave Claude a mass grave of 200 markdown files and now it remembers my entire project between sessions. No cloud, no API keys, one 10mb Go binary, and private. Stateless Agent Memory Engine is your synapse to the CLI.

An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.

A provably read-only SQL layer for AI agents (MCP) and weekly reports — over the database behind an ERP (Logo Tiger, Netsis, Mikro). Statement-checking guard, measured against 28 attacks.

Local-first task and progress database shared by developers and coding agents. Agents claim ready tasks over MCP, record progress and handoffs,and submit commits for independent review; developers confirm, prioritize, and approve work in a local web dashboard. Data stays in a SQLite file inside your project, with no cloud service or account required.

A plug-and-play MCP memory server with pluggable database backends that gives AI coding agents a persistent, shared knowledge graph for teams.

A security filter that blocks dangerous code patterns by comparing normalized structural syntax trees against a blacklist of known threats using vector embeddings. It acts as a gatekeeper to prevent malicious code execution by identifying dangerous structures regardless of specific identifiers or literals.

Provides self-hosted memory management for coding agents via MCP, with local vector storage and tools for adding, searching, updating, and deleting memories.

An advanced MCP server that enables Claude Desktop to act as an autonomous Oracle Database Administrator and Data Analyst with agentic schema discovery and self-healing queries.

A Model Context Protocol server providing LLMs with access to the Ensembl genomics database, enabling AI assistants to query gene information, sequences, variants, and other genomic data across multiple species.