"Browser automation and control for Codex CLI" matching MCP servers:

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

MCP server providing durable Substrate organizational memory tools, including search, read, query, ingest, remember, and sync. It integrates with Codex to automatically capture completed turns and session boundaries for persistent memory.

Enables coding agents to discover, optionally rank, and exactly read bounded source-addressed evidence from large repositories and noisy logs, with local-only privacy controls and quota-aware recovery.

Syncs AI conversations from multiple platforms to local Markdown files for your second brain, and provides browser automation tools via MCP for agentic workflows.

Enables browser-based AI services to connect through remote MCP for internal document search, email checking and replies, timecard, sales/project, schedule/task, and operations tasks. It supports multiple AI clients via compatible remote MCP endpoints.

Connect any AI client to the CaBrain memory system via MCP, exposing tools for memory recall, retain, and brain management.

MCP server that exposes 45 tools for Zotero reference management, enabling AI agents to read/write items, search, extract PDF text, and manage workspaces via the Zotero CLI.

A lightweight, context-efficient CLI and optional stdio MCP server for semantic search, browsing, and writing to your Zotero library.

Enables Codex to run shadow-mode evidence selection by reading source files, scoring passage relevance with Jev or local Eve models, and returning original text with provisional exclusion decisions.

Local-first, durable knowledge-card RAG for Codex, enabling search, retrieval, and maintenance of reusable experience cards.

Enables managing and controlling AnythingLLM instances through MCP, providing tools to list, create, and delete workspaces, retrieve system environment settings, and get vector counts.

MCP for Azure DevOps Boards is a MCP server that lets your favourite AI browse, query and update Azure DevOps work items as if it were a project manager. Written in Rust and optimized for tokens usagem, It runs via stdio or HTTP mode and uses standard Azure authentication with az login.

Implementation of an MCP server for the RAG Web Browser Actor. This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.

A proof of concept MCP server for Apache OFBiz

A local-first MCP server that gives AI coding agents durable project memory, dependency graphs, and impact analysis to answer team knowledge and cross-file change questions before editing.

Transforms static gemini-cli documentation into a queryable RAG service, enabling developers to ask questions about Gemini CLI in natural language and receive instant, accurate answers based on the official documentation directly within their workflow.

Enables asking questions and performing semantic searches against an Inkeep knowledge base. Deployable to Vercel with Next.js.

Provides semantic search, note retrieval, source explanation, daily digests, and health checks for a local Obsidian vault, enabling MCP clients like Claude Desktop and Claude Code to query the second brain via natural language.

Provides project-aware context for coding agents by selecting relevant AGENTS.md, docs, module paths, and decision records based on task, reducing redundant context loading via MCP stdio.

Bridges Google's Gemini CLI with MCP-compatible clients and integrates OpenRouter API for access to 400+ AI models. Provides 33 specialized tools enabling multi-AI workflows, collaborations, and debates between Claude, Gemini, and other LLMs.