"Fluent Bit" matching MCP servers:

Connect AI assistants to Unfold It -- create goals with AI-generated plans, agent-assisted clarification, plan import with enrichment, individual progress tracking, cohort analytics, and skill assessments.

A multi-agent literature review pipeline that uses specialized agents to research, peer-review, and synthesize academic and practitioner perspectives into grounded reports.

Lets MCP clients such as Claude Code, Codex, Cursor, and VS Code drive the Grok Bot desktop app on macOS by listing the user's bots, reading their chats, sending them messages, and answering their multiple-choice questions locally without API keys. All actions run live in the real app via the macOS Accessibility API, with no network calls, telemetry, or dependencies.

MCP server for analyzing successful trading bots on Polymarket, enabling discovery of top traders, AI-powered strategy classification, and bot detection.

Encode, decode, and convert numbers across FP64, FP32, FP16, BF16, TF32, OCP FP8/FP6/FP4, MX, and integer formats, with bit-level breakdowns, rounding modes, and precision-loss analysis. Runs locally; no API key needed.

Enables users to benchmark AI models across English, Urdu, and Roman Urdu by running question sets, grading answers, measuring confidently wrong and hedged responses, and producing reports, comparisons, and CSV exports through an MCP client or CLI.

Enables AI assistants and local workflows to run Jev-powered tools that judge speeches line by line, audit drafts against goals, bisect hard-to-test bugs, simulate common-sense physics, score note pairs, and ask arbitrary typed questions cheaply.

Enables AI coding agents to discover and verify current open-source libraries and models using live GitHub activity, PyPI adoption, license checks, and hardware VRAM estimates before generating code.

Enables AI agents to manage Grok Bots through MCP: create, list, search, and delete bots, send and receive messages, read conversation transcripts, search message history, and check usage.

Enables running open-weight image upscaling and restoration models locally on a Mac's GPU, driven by an MCP client that lists installed models, upscales images, and writes results to a folder as background jobs. Supports tiling for large images, 16-bit input/output, and configurable output scaling so results can be composited pixel-for-pixel over the original.

Provider-neutral short-form AI video toolkit for agents: Sora, Gemini Veo, xAI/Grok and Seedance.

Provides live Bitcoin network data (fees, mempool, hashrate) and AI-powered price/fee forecasts via MCP tools, with free access to basic data and pay-per-call for advanced features.

Converts video and image files through the grey telecinema presets (NTSC-J seated black, 8-bit grey, 1-bit overcalc, and a 4x4 collage), producing silent, dither-free output suitable for AI models to ingest. Every conversion is logged with its full command line to an always-visible SQLite index, so byte and dimension changes between files can be audited at any time.

AI-powered IT support server that understands issues in Turkish and English, suggests fixes, and routes to the right experts via Django DB.

Enables building MCP servers with embedded reasoning, allowing complex tasks to be offloaded to an internal LLM for token and cost efficiency.

Enables users to connect Google Gemini 4 High (Argon Extended Thinking) from Gemini Web into Google Antigravity via MCP tools, a /kg4 slash command, and an OpenAI-compatible proxy for chat completions.

Generates dating profile bios with embedded red flags using the StupidAPIs.

Enables any agent to ask typed questions (Noul, Choice, Score) against Jev's decision model and receive structured answers with probabilities, confidence, and an auditable act/review/abstain decision.

An MCP server that exposes eleven typed decision tools—check, choose, score, judge, route, triage, guard, grep, rank, compact, and ask—so agents can make fast, branchable yes/no, option-pick, score, and filtering decisions on text via TypeSafe's Jev model.

Enables coding agents to query a locally running Kev decision model through MCP tools, returning calibrated probabilities for typed questions such as yes/no, choice, and score.

Enables Codex to delegate tasks to ChatGPT through a browser-backed Oracle connection, with project memory and a verified-result cache. It supports preview, delegation, result polling, and explicit acceptance without an API fallback.

Enables AI assistants to perform typed decisions (choice, score, noul) over text, emails, tickets, or JSON documents, with automatic language routing and source ranking across 100+ languages via a single forward pass.

Enables local AI inference for Claude and Cursor through 22 APIs, including summarization, translation, review, classification, RAG, and more, with all data processed on-device.

Enables MCP clients to ask questions over the indexed document corpus and search handbook passages, returning cited answers and ranked results.

Enables accounts-payable teams to turn emailed or uploaded invoice PDFs into structured, source-cited fields via Claude, run deterministic arithmetic, date, PO and duplicate checks, and route each invoice to a named human for approval or rejection through scoped bearer tokens. Also supports listing pending approvals and forecasting what falls due in the coming weeks, with per-extraction cost tracking.

A comprehensive MCP server for Power BI DAX query execution, validation, optimization, and intelligent assistance with tools for schema analysis, template generation, and health monitoring.

An MCP server integrating Google Gemini LLM for intelligent customer service, providing chat, analytics, and tools for customer data interaction.

Will this AI model fit on your Mac?

Analyzes resume text against job descriptions to provide ATS fit scores, missing keywords, and suggestions.

A remote MCP gateway that lets any MCP client sign in as the end user to discover curated semantic models, read finance glossaries and recipes, inspect schemas and report metadata, and generate or execute DAX through an on-behalf-of token, so row-level security and Build permissions stay enforced. Finance know-how lives centrally in server-side skill files and instructions, so every connected client benefits without per-client configuration.