"Creating a database of novels and screenplays in Google Drive" matching MCP servers:

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 AI agents and MCP clients to drive real Chrome, Edge, Brave, and Firefox browsers through native automation protocols. It exposes tools for navigation, page snapshots, form filling, clicks, screenshots, console/network inspection, and tab management.

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

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

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.

Send email, find out why an email failed, set up sending domains, and manage templates, contacts, lists and campaigns in your AhaSend account.

Self-hosted Nightingale (n9e) includes a native Streamable HTTP MCP server at /mcp for querying alerts, rules, metrics, logs, hosts and dashboards with the caller's existing permissions. Users deploy the Nightingale server themselves; the implementation and deployment documentation are in the main repository, and the official website is https://n9e.io.

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

Enables AI assistants to explore a PostgreSQL database, run bounded read-only SQL, inspect query plans, test hypothetical indexes, find slow queries, and check database health with compact CSV output.

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

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.

Compare service-grant changes, tool alias origins, and saved MCP tool definitions with Gooo rules. Reports preserve incomplete-capture uncertainty and source bindings. No grants are applied and no compared tools are invoked.

Enables agent tools to validate queries, assess token costs, and extract structured datasets from unstructured text using multiple LLM providers.

Serves the review notes left at lines of a diff in seam, a terminal diff viewer, to an agent with the code around them. The agent answers each note, and the answer shows in seam at that line.

MCP server for GLEIF LEI (Legal Entity Identifier) database access. Look up, validate, and search legal entities and their relationships in the global LEI system.

Fork, break, and revert real VirtualBox VMs as MCP tools; drive GUI-only guests through the hypervisor (screenshot, click, type, keys) with nothing installed in the guest. Windows host with VirtualBox.

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

Lets AI agents drive terminal apps built with Limoni (a Go TUI engine) through their semantic tree instead of scraping the screen: widgets are found by role and label, clicked, typed into, and waited on. Runs locally over the app's automation socket; secret fields never reach the agent.

A persistent, Git-versioned map of your whole codebase and database schema that coding agents read before they touch anything. Local-first MCP server + CLI in Go: a governed repository index of code knowledge that gives Claude Code, Codex, Cursor, and opencode long-term context, memory, and code intelligence.

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.

Enables AI assistants to manage and query Tiger Cloud database services, including service lifecycle operations, database connections, and SQL execution.

Bridges MCP clients that require stdio to a running pREST HTTP MCP endpoint, enabling database interaction via natural language.

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

Control-plane proxy that sits in front of MCP servers, enforcing per-identity policy (YAML/OPA/Cedar), budget limits, and an audit trail on every call. Includes real-time anomaly detection that auto-blocks a compromised agent without a human in the loop.

Enables AI tools to query a PostgreSQL database, read its schema, list and describe tables, and explain queries while enforcing read-only transactions, row and byte limits, and timeouts.

Connect to your TTRPG campaign's repository and database. Instead of retrieving prose, its 48 tools (20 read, 28 write) return typed state: 14 entity schemas (NPCs, factions, locations, sessions, lore), relationship and knowledge-graph queries, wiki blocks, and a narrative-state bundle of open threads and canon facts.

Description: Introduce Beelzebub, an MCP‑based honeypot framework that enables creating decoy tools to detect prompt injection and malicious agent behavior. Motivation: Strengthen the security of LLM workflows by adding a non‑intrusive detection mechanism.