"Improving the Thinking Capabilities of My Gemini AI" matching MCP servers:

Integrates Google's Gemini API to provide sequential analytical thinking and problem-solving capabilities with meta-commentary, confidence levels, branching thoughts, and session persistence for complex problems.

Provides MCP tools to search, retrieve, and answer questions from the public Open Finance Brasil Confluence documentation using BM25-based local indexing.

Enables interaction with Google's Gemini AI models including file uploads, conversation management, and batch API processing for large-scale tasks at reduced costs. Supports multiple Gemini models with advanced features like embeddings generation and automated workflow processing.

Gemini MCP with image, video, svg, landing page generation and search. Grounded search, deep research, image generation... Having them as tools inside Claude beats switching between browser tabs.

Enables multi-turn conversations with Google Gemini AI models, supporting file and image analysis, automatic model selection, deep thinking mode, and Google Search integration through the AIStudioProxyAPI backend.

A TypeScript Model Context Protocol (MCP) server to allow LLMs to programmatically construct mind maps to explore an idea space, with enforced "metacognitive" self-reflection.

Enables AI-powered web searches using Google's Gemini 2.5 models with Google Search Grounding. Supports multiple Gemini models (Flash, Flash-Lite, Pro) with configurable thinking budget and web search capabilities.

A Model Context Protocol server that enables Claude Desktop and other MCP-compatible clients to leverage Google's Gemini AI models with features like thinking models, Google Search grounding, JSON mode, and vision support.

Enhances AI model capabilities with structured, retrieval-augmented thinking processes that enable dynamic thought chains, parallel exploration paths, and recursive refinement cycles for improved reasoning.

A server that provides access to Google Gemini AI capabilities including text generation, image analysis, YouTube video analysis, and web search functionality through the MCP protocol.

An MCP tool enabling structured thinking and analysis across multiple AI platforms through branch management, semantic analysis, and cognitive enhancement.

Turns local Codex session transcripts into a searchable memory that MCP-compatible coding agents can query to retrieve relevant past sessions or exact commands and fixes.

Enables AI assistants to perform real-time internet searches and get AI-powered analysis of current information through the gemini-cli tool.

A customizable Model Context Protocol server built with mcp-framework that enables Claude to access external tools and capabilities through a standardized interface.

An autonomous AI development agent that enables full-stack coding, automated verification, RAG-powered code search, and quality assurance through MCP tools. Supports Gemini CLI, Claude Code CLI, with features like parallel verification, security scanning, and spec-driven development.

Enables semantic search over local knowledge bases like Obsidian notes, SQLite, and plaintext files, exposing results to Claude via MCP server.

Provides search and retrieval over a local database of Pathfinder 2e rules. Enables Claude Code to answer rules questions with cited, accurate answers from fetched entries.

Enables agents to search a local, fully offline personal document library (Markdown/txt/PDF/docx) via SQLite FTS5 trigram search with subject-terminology expansion, returning every hit with its domain, document title, section path, and page or offset provenance. It also exposes domain statistics, incremental ingestion, and document deprecation as tools, alongside a read-only, runtime-persona-scoped ask/coverage mode.

An advanced MCP server that implements sophisticated sequential thinking using a coordinated team of specialized AI agents (Planner, Researcher, Analyzer, Critic, Synthesizer) to deeply analyze problems and provide high-quality, structured reasoning.

A dedicated server that wraps Google's Gemini AI models in a Model Context Protocol (MCP) interface, allowing other LLMs and MCP-compatible systems to access Gemini's capabilities like content generation, function calling, chat, and file handling through standardized tools.