"A collaborative workspace and documentation tool" matching MCP servers:

Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.

Lets a human review what an AI agent is about to post to a chat tool (Slack first) before it is sent. Renders the draft, destination and warnings (@here/@channel, unresolved mentions, format issues) in a neutral local HTML preview; never sends anything.

CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.

MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.

Multi-account Google Workspace MCP server — Gmail, Calendar, and Drive with smart routing.

Provides access to your VictoriaTraces instance and seamless integration with VictoriaTraces APIs and documentation for querying traces, services, and operations.

Provides structured, tool-based access to a Honeybadger account's API, enabling users to browse projects, inspect faults and notices, work with dashboards, alarms, and check-ins, and retrieve reference documentation such as BadgerQL. Runs in read-only mode by default, with optional write and delete operations, and can connect either through the hosted OAuth endpoint or a self-hosted stdio/Docker deployment.

Enables AI coding assistants to search and retrieve information from a locally ingested knowledge base using hybrid search, grounded in user-curated documentation.

Enables AI assistants to manage Trello boards, cards, checklists, comments, and attachments over local stdio, with compact curated responses. Supports workspace allowlists, tool selection profiles, and an opt-in read-only mode for safer access.

An MCP (Model Context Protocol) server for managing Tailscale resources using the official Tailscale Go client library v2. This server provides complete coverage of the Tailscale API with enhanced, self-descriptive tools powered by OpenAPI documentation.

Enables AI agents to read and edit entity-relationship diagrams and SQL database schemas on the liz-whiteboard collaborative whiteboard through natural language, supporting table, column, and relationship management.

A powerful MCP tool for forging and managing AI agent personalities with customizable expert traits and behaviors.

This is a Model Context Protocol (MCP) server implemented in Go, providing a tool to analyze Go pprof performance profiles.

godoc-mcp is a Model Context Protocol (MCP) server that provides efficient access to Go documentation. It helps LLMs understand Go projects by providing direct access to package documentation without needing to read entire source files.

Provides 23 bounded MCP tools for AI agents to perform technical SEO audits, including crawl setup, page analysis, issue detection, and report exports, all while keeping data local.

CodeMCP — a secure, workspace-bound bridge between your machine and ChatGPT, Claude, or any AI agent.

MCP server for a local-first messaging workspace that integrates Google Messages, WhatsApp, and Signal. It enables reading, sending, searching messages, and managing conversations through MCP tools.

A gateway service that connects AI assistants to numerous external tools like Notion, GitHub, and Google Workspace through a single Model Context Protocol endpoint. It provides a centralized hub for managing multiple tool integrations with secure authentication and a unified API architecture.

An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.

ContextLattice is an HTTP-first, MCP-compatible memory/context/task orchestrator that persists writes and returns fused recall from specialized stores with local-first defaults. Primary URL: https://contextlattice.io/ Install: https://contextlattice.io/installation.html Troubleshooting: https://contextlattice.io/troubleshooting.html