"Google Tasks" matching MCP servers:

MCP server that exposes Google Jules AI agent as tools, allowing local AI agents to list authorized repositories and delegate coding tasks to Jules, receiving session URLs for tracking.

Enables AI tools to perform real-time Google Search with grounded answers and inline citations, free with a Google account.

Enables AI assistants to manage tasks, projects, and dependencies through MCP protocol with embedded Web UI, multi-workspace support, and Turkish language capabilities for productivity tracking.

Enables finding files and knowing their location and permissions, organizing folders, moving and copying content, transferring files in and out, managing sharing with transparency, tracking changes, and handling shared drives.

Enables reading, searching, and writing to Google Chat spaces, direct messages, and sidebar through MCP clients such as Claude Code and Claude Desktop.

Provides access to Google Calendar, enabling listing calendars and events, checking availability, creating and updating events, and managing sharing through MCP.

Enables natural-language interaction with Gmail, including reading, searching, drafting, and managing emails, with safety features like read-only mode and bounded reads.

Enables reading and writing spreadsheet ranges without destroying formulas, plus reshaping, formatting, and validating data within a spreadsheet.

Enables reading, editing, suggesting, and commenting on Google Docs from any MCP client, with scoped reads, minimal-diff edits, and support for tables, tabs, and layout.

Enables AI agents to create, manage, and track tasks within plans using Valkey as the persistence layer. Supports plan and task management with Markdown notes, status tracking, and prioritization through multiple transport protocols (SSE, Streamable HTTP, STDIO).

MCP server for AI-powered web research — search (Google, Brave, Serper, SearXNG), scrape any page, extract PDFs/DOCX/YouTube transcripts, academic & patent search. Single Go binary. Works with Claude, Cursor, Copilot, and any MCP client.

MCP server for Directum RX (ECM/BPM): assignments, tasks, documents and their text, knowledge base, agile boards, project plans, any entity via OData, and search over the system help of your own RX version. Read-only by default; write tools are behind a flag and ask for confirmation.

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

MCP server for patent search and prior art discovery powered by Google Patents public dataset on BigQuery. Supports searching patents, fetching full patent details with CPC codes and citations, and retrieving legal claims text.

Local MCP server for plain Markdown notes: list, read, create and search notes, and manage their tasks and Kanban board (move cards, toggle tasks, set start and due dates).

A local workspace whose accessible pages and MCP tools are generated from the same definitions, so AI agents can do everything a person can: create, update and find notes, tasks and projects, build and arrange pages, and read any page back as a screen reader gets it.

A fast, lightweight MCP server and CLI for Obsidian vaults built in Go. 16 multiplexed tools covering 72 actions for notes, search, templates, tasks, links, frontmatter, and vault analysis. Single binary, no plugins required.

Manage a fleet of OPNsense firewalls from an AI agent, inside guardrails it can't drive around. MCP server for central management of OPNsense firewall fleets. 129 tools across devices, config sync, tasks, schedules, templates, backups and remote consoles - destructive actions confirmation-gated, MCP-issued tokens lifetime-bounded, backup and storage secrets excluded from the toolset entirely.

MCP server for managing Apple Wallet and Google Wallet passes via the PassNinja API. Provides tools to create, list, update, and delete pass templates, passes, and webhooks.

Content-addressed code graph that produces ranked context for AI agents in one call. 22 MCP tools across indexing, blast radius, test scope, semantic diff, runtime traffic, and feedback-aware context packing. Incremental updates via Merkle DAG (no re-indexing). GCF wire format saves 84% tokens vs JSON