Desktop Commander MCP

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.

Awesome MCP Servers is a curated collection of Model Context Protocol (MCP) server implementations, maintained as a GitHub repository with a synchronized web directory. It catalogs production-ready and experimental servers that let AI models interact with local and remote resources through standardized interfaces, including file access, databases, API integrations, browser automation, cloud platforms, research services, and other contextual tools. The repository organizes entries by capability, programming language, deployment scope, operating system, and whether an implementation is official.

An MCP server from Zapier that connects authenticated applications so compatible AI tools can access and use them through a single integration layer. It supports clients including Cursor, Claude Code, and Codex.

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.

BankMCP is a self-hosted, read-only Model Context Protocol server that lets AI assistants query a user's bank accounts through Enable Banking's PSD2 open-banking API. The user authenticates at the bank through a consent flow; BankMCP stores consent and account metadata but does not store balances or transactions, make payments, or send telemetry. It exposes MCP tools for managing bank connections and accounts, retrieving balances and paginated transactions, and creating rules that poll accounts for conditions such as low balances or matching payments and send webhook notifications. It can run locally or on a server, is distributed as the npm package `bankmcp`, supports standard MCP clients including Claude and Ollama, and is licensed under the MIT License.