"Connecting to Gemini Flash Experimental" matching MCP servers:

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.

Experimental MCP server for the wflow.com public API, enabling natural language operations on documents, registers, users, roles, and teams across one or many organizations.

This MCP server lets AI agents connect to Figma to read, analyze, create, and modify designs, including elements, styles, assets, and code generation. It works with free Figma accounts and supports parallel multi-agent use across MCP-compatible clients.

Connects MCP clients to Gemini Cloud Assist APIs, enabling users to understand, manage, and troubleshoot their Google Cloud environment using natural language.

Enables agents to transform tabular Markdown content into structured, type-inferred records with normalized formatting through an MCP-compatible interface.

Enables converting Markdown and HTML tables into structured JSON records with automatic column type inference and format normalization. It also offers supporting web-agent primitives such as DOM semantic pruning, form field auto-mapping, and execution trajectory evaluation, all via a zero-dependency MCP server.

Enables agents to break high-level business objectives into dependency-ordered sub-task graphs and then directly generate the finished deliverables, such as financial spreadsheets, executive presentations, and analytical reports. It runs as a zero-dependency Python MCP server over JSON-RPC stdio, adding deterministic authorization, role-boundary validation, and telemetry.

Thin MCP server that enables AI agents to generate video, image, and audio content via the Deepy API using a personal API key, with safe generation flow and no business logic.

Enables querying of a locally pinned snapshot of the Education-to-Workforce Indicator Framework — 99 indicators and 11.8M observations — to browse questions, describe metrics, resolve places, and fetch or rank data across national, state, county, and district levels.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

Enables agents to discover available still-image animation models, obtain credit quotes without charge, submit one explicitly approved generation job, and poll the resulting short clip.

Enables Gemini to read verified company facts, sources, provenance, and confidence from AuthorityPrompt for any published company domain.

Enables searching government awards through the Sell to State API by proxying JSON-RPC to the live HTTP MCP endpoint, requiring an API key.

Connect Gemini CLI to any ObjectStack deployment over the Model Context Protocol to discover objects, query and change records, and run business actions under your own permissions and row-level security.

Lightweight project management for teams and AI agents.

Enables checking a verified email for breach exposure and querying SHA-1 password hash prefixes through read-only tools that return concise evidence summaries.

Experimental Model Context Protocol server that enables access to JFrog Platform API capabilities including repository management, build tracking, artifact searching, and package security analysis.

Experimental server that implements the Model Context Protocol (MCP) for Nylas API, providing resources, tools, and prompts to help developers integrate email, calendar, and contacts functionality with AI applications.

Enables connecting to CompanyGraph's mental-model as a remote MCP endpoint, allowing agents like Claude, ChatGPT, and Gemini to query the model's types, schemas, rules, and entities without authentication.

Neo4j MCP Canary is a fast-moving, experimental release of the Neo4j MCP server for customers who want to explore emerging capabilities before they are considered for the official server.