#seq

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

MCP server for AI Diagram Maker — generate software engineering diagrams from natural language, code, ASCII diagram, images, or Mermaid. Inline diagram rendering using MCP apps UI and diagram URL in responses. Works with Cursor, Claude Desktop, Claude Code, and any MCP-compatible AI.

Reply.io is a sales engagement platform used by thousands of B2B sales teams to automate multichannel outreach — email, LinkedIn, calls, SMS, and WhatsApp. The Reply.io MCP server exposes the platform's core functionality as tools that any MCP-compatible AI model can call directly. Once connected, your AI assistant can list and manage sequences, pull real-time performance analytics (delivery, open, reply, and click rates at the sequence and step level), enroll contacts, and control campaign state — all through natural language, no browser required. Typical use cases: - Ask Claude or Cursor to pull open and reply rates for your active sequences and identify underperformers - Enroll a new contact in a sequence mid-conversation, without switching to the Reply.io dashboard - Pause or start sequences, then check step-level stats to diagnose drop-off points - Build AI agents that automate outreach workflows end-to-end — prospect, enroll, follow up, analyze The MCP server is hosted by Reply.io and authenticated via API key. No self-hosting or open-source setup is required.

[GET API KEY AT https://www.the-thoughtbox.dev/] Thoughtbox is a reasoning ledger and context engine for AI agents. It provides structured reasoning tools, enabling agents to think step-by-step, branch into alternative explorations, revise earlier conclusions, and maintain a persistent record of their cognitive process.

Enterprise-Grade HR Assistant leveraging Model Context Protocol for seamless employee data and HR policy queries

An enhanced version of the original mcp-sequentialthinking-tools by Scott Spence. This enhanced version significantly improves the original framework with improved utilization of branching, revisiting, and thought revision. Thoughts are much more dynamic and intentional, spread out throughout the conversation at the correct time. There is also caching for tools and thoughts, session continuation and context management, and a bunch of other improvements.

MCP server for trajectory inference using cellrank

MCP server for CNV analysis using infercnv

MCP server for scanpy

MCP server for cell–cell communication using liana

Datalust Seq Server API wrapped as an MCP

An advanced sequential thinking process using a Multi-Agent System (MAS) built with the Agno framework and served via MCP.

Mirror of

MCP server to interact with LogSeq via its Local HTTP API - enabling AI assistants like Claude to seamlessly read, write, and manage your LogSeq graph.

Taking the sequential thinking mcp server and prodding it onwards.