"Character Name and Profile Generator" matching MCP servers:

Exposes a curated professional knowledge base as read-only tools so any MCP client can pull a profile summary, search documented experience, browse case studies, and check rates and contact details in English or Spanish. Every answer is drawn only from the published documents and declines questions the corpus does not cover.

A self-contained Claude Code plugin that profiles a project by running a fixed DAG to emit agent-facing context pages, a human/developer guide, and a queryable vectorstore.

Serves plain-text notes that an Obsidian user has explicitly published for AI over streamable HTTP, with full-text and embedding-based search. MCP clients can read and search those notes and queue suggested edits that the user's own client applies only if the AI rules allow it.

Generates RAG pipeline configurations from natural language descriptions, providing recommendations for chunking, embeddings, and vector stores.

Generates crash-proof Python LLM pipelines from plain English descriptions. Pipelines resume from the last successful node after a crash instead of restarting from scratch. IProvider-agnostic , works with Groq, Gemini, Ollama, OpenAI, or any Python callable. Zero infrastructure, runs entirely on free-tier APIs.

An MCP-compatible server that provides tools for integrating selected Postman API requests, allowing LLMs like Claude to interact with APIs through natural language.

Generates production-ready short video scripts from real-time web search data using Tavily and Gemini, exposed as MCP tools.

CTX is a tool made to solve a big problem when chatting with LLMs like ChatGPT or Claude: giving them enough context about your project.

Upload Word, Excel, PDF, or PowerPoint documents to a vector RAG store with vision-model extraction, then search semantically and retrieve chunks with page numbers for precise citations.

Enables AI clients to search a personal corpus, read relevant source passages, and answer questions with traceable evidence from imported sessions, notes, and articles.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

Processes documents, analyzes GitHub repositories, and researches companies using local Gemma3 AI to extract structured business insights for generating compelling case studies.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

Automatically generates typed React hooks for Next.js projects by crawling API routes, GraphQL queries, and components. Analyzes pages to suggest optimal render modes (SSR/CSR/ISR) and produces comprehensive documentation with AI-powered guidance.

Provides structured dealer brand data including inventory, promotions, reviews, and dealer profile via MCP tools, enabling LLMs to answer accurate brand-related queries.

An MCP server implementation that enables generation of Google Ads content through Claude Code, Claude Desktop, and other MCP-compatible clients.

A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.

MCP server for the DeepGHS anime AI ecosystem. Dataset discovery, tag search, character dataset finder, and training pipeline code generation.

Enables Claude AI to seamlessly interact with Scrivener projects for document management, AI-powered content analysis, and advanced writing assistance.

AI-powered code generator for the Arbitrum ecosystem with 19 MCP tools. Generates Stylus smart contracts (Rust/WASM), SDK bridging code, full-stack dApps, and Orbit chain deployments using RAG-based retrieval over Arbitrum documentation.

Enables persistent, model-driven text adventures with transactional saves, character knowledge boundaries, cited canon retrieval, dice outcomes, and forkable historical timelines via MCP tools and local SQLite storage.

Enables scoped project discovery, deterministic rule and profile management, and durable automation with trigger/pause/resume/cancel and audit history for approved project contexts.

Local MCP server exposing the dek-memory hybrid memory engine over stdio, with optional ChatGPT tools for managing account memories via a browser profile.

Enables to search, draft, and profile from your X/Twitter archive locally via MCP tools.

MCP server for searching files on macOS by name or content using semantic and lexical search, providing file paths and line numbers for agents to read from.

Gives Google Antigravity persistent memory by automatically recalling profile and project context before model calls and saving new conversation turns at turn boundaries. Exposes MCP tools to add, search, list, profile, and forget memories, with privacy filtering and per-repository scoping.

Enables AI assistants to access a Markdown persona pack through MCP, providing work briefs, draft reviews, example lookup, and profile resources so generated work follows the user's decision principles, quality standards, and voice.

The personal context layer for AI - one user owned profile plus files, read by any MCP client so you never re-introduce yourself.

Enables LLM agents to search canon works, lock timeline-scoped rules and character seals, audit plots for out-of-character or canon-breaking content before writing, and generate divergent worldbuilding hooks.

Enables agents to view active beliefs, read owner-selected source text, submit inferred extraction for selected sources, and consult bounded choices from a local personal profile.

Enables job seekers to structure job descriptions, search a personal Markdown profile with hybrid BM25/dense retrieval, and compare a posting against that profile to see which requirements are supported, weak, or missing evidence. It also tracks applications and follow-up deadlines through JSON-backed tools whose writes stay as previews until a human turn confirms them.

Enables Google# MyData from (JSON (server name is

Enables MCP clients to generate diverse hypothetical answer passages from sparse user queries, improving vector search recall by bridging lexical and semantic gaps.

Enables conversational queries about a GitHub user's profile, using lazy indexing and tool calls to retrieve repository info and file contents, with cached results for efficiency.

An AI-native Weiterbildung discovery layer over Mein NOW course data, providing tools for course search, profile matching, and fit explanation via MCP.

Enables clients to transform sparse user queries into multiple hypothetical answer passages from different perspectives, improving dense retrieval and vector search recall. Exposes this capability through MCP JSON-RPC 2.0 tools with no external dependencies.

Enables secure, high-concurrency AI integrations through MCP, providing semantic document search, SSRF-protected external context fetching, and cached user profile retrieval.

A local decision graph built from your repo's git history, PRs, ADRs and CLAUDE.md/AGENTS.md, plus Jira, Linear, Notion, Slack and others read-only. Coding agents query it for what was decided and why, and every edit is checked against it before it is written.

An MCP server that provides targeted PostgreSQL schema access to AI agents, retrieving only relevant tables for a question and enforcing read-only access through multiple layers.

The open-source, self-organizing memory for all your AI tools. Persistent memory over MCP (remember, recall, observe): background agents extract entities, resolve conflicts, and keep cited syntheses current in an append-only, encrypted, single-tenant vault.