"Creating files in Xcode development environment" matching MCP servers:

Enables LibreChat agents to manage per-user private files, persistent documentation, RAG indexing and semantic search, and publish files via secure opaque public links.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

A lightweight, dependency-free MCP server that answers cited queries over a Tero corpus index.json via stdio JSON-RPC 2.0, with honest refusal semantics and no silent empty results.

MCP server for Google's Gemini File Search (RAG). Manage file search stores, upload documents, and query with RAG through 12 tools.

A Node In Layers package that simplifies creation of MCP (Model-Control-Protocol) servers with tools for defining models, adding CRUD operations, and interacting with clients.

Provides tools for searching Agent8 game development code examples and system prompts to assist in Agent8 SDK development.

Enables searching and retrieving documents from a local folder to ground LLM answers in your files.

A local MCP server that indexes files in a directory using Gemini Embedding 2, enabling AI agents to perform semantic search over local documents.

A lightweight server that provides curated, high-quality prompts for common development tasks like UI/UX design, project setup, and debugging to enhance AI-powered development workflows.

Provides structured web search capabilities optimized for technical and software development content via providers like OpenRouter. It enables AI agents to perform research and retrieve relevant technical data in a consistent, programmatic JSON format.

Enables running multiple Claude prompts simultaneously in parallel with support for file contexts and output redirection to individual files.

A Python server implementing the Model Context Protocol to provide customizable prompt templates, resources, and tools that enhance LLM interactions in the continue.dev environment.

Enables AI assistants to interact with Tencent Lexiang enterprise knowledge base for searching, reading, creating, and editing documents, managing files, and importing meeting recordings.

Enables storing, searching, and discovering knowledge connections using associative memory, with semantic search, hierarchical organization, and cross-environment sync.

he Maximo MCP Server bridges AI agents (Claude, Cursor, Antigravity) with your IBM Maximo environment. It empowers your AI to autonomously discover Object Structures (APIs), inspect schemas, and query live data via OSLC. Instead of hallucinating field names, the AI validates queries instantly and ca

Enables AI development tools to perform semantic search and document relationship analysis on vectorized content stored in Qdrant databases.

A Model Context Protocol server integration that creates a persistent, searchable working memory for AI-assisted development by enabling automated context recall and knowledge persistence in Chroma, the open-source embedding database.

A Model Context Protocol (MCP) based server that efficiently manages PDF files, allowing AI coding tools like Cursor to read, summarize, and extract information from PDF datasheets to assist embedded development work.

Context Portal (ConPort): A memory bank MCP server building a project-specific knowledge graph to supercharge AI assistants. Enables powerful Retrieval Augmented Generation (RAG) for context-aware development in your IDE.