"Information on Podman" matching MCP servers:

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

DevsContext is an MCP server that provides AI coding agents with synthesized engineering context—requirements, decisions, architecture, and standards—from tools like Jira and Slack. It fetches and synthesizes relevant information on demand to help agents work on tasks correctly.

Provides persistent, searchable memory for AI agents, enabling them to retain, recall, and reflect on information across conversations.

A remote MCP server providing a tool for searching and querying ATprotocol documentation, helping developers easily access information while building on the protocol.

An MCP server that provides semantic memory on top of Qdrant vector search, with tools to store and retrieve information using embeddings.

Enables storing and retrieving text passages based on semantic meaning using local embeddings (Ollama) and vector storage (ChromaDB), allowing conversational memorization and retrieval of information.

A Model Context Protocol server that runs on Cloudflare Workers with OAuth login, allowing clients like Claude Desktop to connect to it for tool-augmented AI interactions.

This read-only MCP Server allows you to connect to Act-On data from Claude Desktop through CData JDBC Drivers. Free (beta) read/write servers available at https://www.cdata.com/solutions/mcp

Utilizes Gemini API and Google Search to generate answers based on the latest information for user queries.

MCP server that provides secure access to a serverless Markdown wiki on AWS, enabling AI assistants to read, search, and edit pages with space-level permission checks and Bedrock-powered semantic search.

Enables MCP clients to remember user information, preferences, and behaviors across conversations using vector search technology. Built on Cloudflare infrastructure with persistent storage and semantic similarity matching.

MCP Memory is an MCP Server that gives MCP Clients the ability to remember information about users across conversations. It uses vector search technology to find relevant memories based on meaning, not just keywords.

Enables AI assistants to remember user information and preferences across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage.

A personal second brain on Cloudflare Workers that stores knowledge as a semantic graph with auto-linking, deduplication, and MCP tools for AI agents to save, search, and connect information.

Provides 78 tools for AGI experiments based on universal physics principles like entropy and criticality. It enables advanced long-term memory management, diversity-focused information retrieval, and meta-cognitive monitoring for self-improving AI systems.

Gives AI agents a private, on-device persistent memory using semantic search over stored facts, preferences, and decisions. It enables agents to remember information, recall it by meaning even without keyword overlap, delete memories, and list them by tag.

Enables querying live Zora token data and analytics methodology through SQL and document retrieval tools, providing guarded access to on-chain holder, transfer, and token information.

A token-optimized documentation and Q&A registry for AI agents, providing dense machine-readable symbol-level docs and agent-contributed Q&A to minimize token usage while preserving information.

Enables AI assistants to remember user information across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage and retrieval.

Enables MCP clients to remember user information, preferences, and behaviors across conversations using vector search technology. Built on Cloudflare infrastructure with AI-powered semantic search to find relevant memories based on meaning rather than keywords.