"Methods for Parsing Emails" matching MCP servers:

Stop paying for your agent to rediscover what other agents already figured out. Prior is a shared knowledge base where agents exchange proven solutions — one search can save 10 minutes of trial-and-error and thousands of tokens. Your Sonnet gets access to solutions that Opus spent 20 tool calls discovering. Search is free with feedback, and contributing earns credits.

Enables users to visualize the impact of edits in internal documents and emails by structuring content as a graph and tracing dependency chains.

MCP server for parsing, searching, and extracting branches from XMind mind map files, supporting Markdown/JSON output, token-aware formatting, and Claude Desktop integration.

An MCP server that exposes the markdown issue tracker under .scratch/ as a queryable graph, letting agents see open, blocked, or takeable issues without re-parsing prose.

A knowledge-based MCP server for Ozon sellers, enabling AI agents to search a 42-lesson Chinese operations playbook and discover/call over 460 Seller and Performance API methods for real business actions.

Enables management of Amazon Bedrock Knowledge Bases including creation, data source configuration, document ingestion, and RAG (Retrieval-Augmented Generation) queries with support for multiple embedding models and custom parsing/chunking strategies.

A local semantic memory and code-indexer that uses AST parsing for structural understanding and persists architectural decisions to help AI assistants bypass context window limits.

Local-first personal memory for AI agents. Captures your Feishu chats, emails, meetings, and AI coding sessions into a private memory graph, and serves it to any agent over MCP.

A public MCP server about Boris Churzin's builds, decisions, and ops doctrine, allowing agents to interrogate his judgment instead of parsing a PDF.

An MCP server for Claude Code that enables semantic search of past session transcripts and intelligent session forking, allowing users to find and resume from relevant previous conversations with full context.

Enables AI agents to record and rank learnings, facts, and methods through a collaborative voting framework. It provides tools for agents to surface the most useful information across sessions using persistent memory storage.

Interacts with LogSeq via its API.

Enables exploration and organization of research ideas using a hierarchical tile-based method with support for creating interconnected nodes (questions, hypotheses, methods, results), analyzing research gaps, and exporting to multiple visualization formats.

A design knowledge MCP server that Claude can query when generating UI, covering eight layers: principles, patterns, content design systems, research methods, service design, brand/visual, business strategy, and design tokens.

A read-only MCP server that provides document awareness for agents by parsing local files into structured profiles, blocks, chunks, and search results, enabling agents to understand and cite document content without dealing with raw file formats.

Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.

An MCP server that provides Claude Code with 99 methodology skills, seed patterns, decision logging, and memory tools to improve software development decisions. It acts as a cognitive scaffold layer, enabling better working methods rather than just additional data.

Enables Claude to search and analyze Obsidian vault content using ripgrep with support for wiki links, backlinks, frontmatter properties, orphaned notes, and intelligent context detection showing which heading or property contains each match.

Enables quant research organizations to log hypotheses and outcomes, count trials for honest statistical verdicts, explore novel methods, run significance gates, and evolve reusable skills from validated trajectories, all backed by SQLite.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.