Enables AI agents to read Logseq notes, journals, tasks, pages and blocks—including embedded screenshots as viewable images—directly from the on-disk graph. It works read-only with Logseq closed and no network access, snapshotting the database so nothing can be modified.
Python stdio MCP server that interfaces with the Logseq local HTTP API, enabling tools to manage pages, blocks, queries, and graph configurations in Logseq.
An MCP server that lets an AI agent operate a Logseq (DB) graph through safe, high-level tools for reading and managing notes, tasks, and projects without needing to know Logseq's internals.
Queryable UniFi API documentation for Network, Protect, Site Manager, InnerSpace, Mobility and Carrier Fabric - endpoint search, schema drill-down and code examples in five languages. Read-only: it serves scraped docs and never connects to a controller.
A Model Context Protocol server that enables AI agents to interact with a local Logseq instance, allowing operations like creating pages, managing blocks, and searching across a knowledge graph.
A Model Context Protocol server that enables AI agents to interact with local Logseq knowledge graphs, supporting operations like creating/editing pages and blocks, searching content, and managing journal entries.
Enables interaction with your Logseq personal knowledge management system via MCP, allowing retrieval of tagged notes and todo lists through Logseq's HTTP API.
A server that enables users to chat with each other by repurposing the Model Context Protocol (MCP), designed for AI tool calls, into a human-to-human communication system.
Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.
Deterministic SNAP eligibility logic, exposed as auditable Model Context Protocol tools. An AI agent can read, reason, and orchestrate, but the eligibility determination itself is made by versioned, tested, cited code that a caseworker, an auditor, or a court can inspect.
Provides a SQLite-backed MCP server that records agent memory as history, enabling explicit consolidation, source checks, revisions, narrative versions, and accountable forgetting.
Enables interactive command-line chat with AI models via the Anthropic API, supporting document retrieval with @mentions and slash-command prompts with tab auto-completion.