"Elm" matching MCP servers:

Enables fast, on-device machine learning with production-grade persistence through the Model Context Protocol. It allows instant training of text classifiers using Extreme Learning Machines, with SurrealDB-backed persistence and monitoring.

Lets MCP clients delegate private or bulk text tasks to a local OpenAI-compatible LLM while keeping data on the machine.

Enables agents to detect and redact PII and secrets in text, HTML, and PDF documents before they reach an LLM, with reversible placeholder, mask, or hash redaction, and to list supported detectors and redaction styles.

MCP server that completes prompts with automatic provider fallback across OpenAI, Anthropic Claude, and Google Gemini. It is rate-limit aware, retries on transient failures, and provides a transparent attempt log.

Enables Claude Code to use GLM (Zhipu) as a cheap, full-capability subagent for file editing, code generation, and bash commands, with automatic routing between Opus and GLM based on task complexity.

Provides a vision tool that converts images into structured text descriptions and OCR using the free GLM-4.6V-Flash model, enabling text-only LLMs like DeepSeek to understand images.

Independent latency and uptime data for 46 hosted AI inference APIs, probed every 5 minutes from 4 regions with no gateway, plus a verified model deprecation calendar and Claude Code / Codex speed and accuracy drift. Four read-only tools, no API key; data CC BY 4.0.

Enables text-only reasoning models to see images by wrapping vision-language models as MCP tools, supporting image description, OCR, chart analysis, and custom questioning within MCP-compatible IDEs.

MCP server that provides tools for evaluating LLM agent reliability, including adversarial task generation, automated LLM-as-judge assessment, and confidence statistics.

Manages brand monitoring projects, runs scans across 350+ LLMs, and analyzes results through natural language.

Exposes Z.ai GLM models (GLM-5.3 and siblings) as callable tools within Claude Code and Claude Desktop, enabling large-context second opinions, bulk grunt work, and independent model reasoning mid-conversation.

An MCP server that runs curated adversarial prompts against local Ollama models to test guardrails, scoring responses with heuristic verdicts for human review.

A drop-in MCP vision server for Zhipu GLM Coding Plan, offering 8 vision tools powered by glm-5v-turbo with smart retry and caching.

Enables cloud-based MCP clients to delegate privacy-sensitive or large-output tasks to a local LLM, returning sanitized placeholders or digested summaries so private data never leaves the user's network.

An MCP server providing vision and video analysis tools, configurable with any model provider.

Enables MCP clients to send raw text prompts to inexpensive LLM models via the Devin/Windsurf backend, returning answers in result files to avoid context bloat, with support for multi-turn sessions and model discovery.

A thin MCP server that delegates lightweight tasks from Claude Code or any MCP-compatible client to local or cloud LLMs via LiteLLM, supporting models like Ollama and cloud APIs as subagents.

A Model Context Protocol server that wraps the free GLM-4.6V-Flash vision model, enabling text-only LLM clients like Codex, Cursor, and Claude Desktop to analyze images, videos, and files (PDF/TXT) through standard MCP tools.

Enables AI agents to convert images and PDFs, including large scanned books, into Markdown through GLM-OCR, with support for long-image slicing, progress tracking, and asynchronous OCR tasks.

MCP server that exposes GLM-4.6V-Flash (free vision model) image analysis to any MCP client, supporting single/multi-image analysis, OCR, and multi-image comparison via an analyze_image tool that accepts local paths, HTTP(S) URLs, or base64 data URIs, with rate-limit resilience and multi-key failover.