"KLM" matching MCP servers:

Gives text-only LLM coding agents vision by routing images to a multimodal model and returning detailed textual descriptions. Supports local files, URLs, clipboard, base64, raw bytes, and multiple providers like OpenAI, Anthropic, and Gemini.

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 delegating coding tasks to isolated Claude Code subprocesses billed against a GLM Coding Plan, with tools to delegate, await, continue, list, cancel, and inspect runs.

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.

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.

Provides persistent browser tabs with tools to read, click, type, and interact with web pages, enabling local LLM agents to perform multi-step web tasks.

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

Atlas Cloud MCP Server enables developers to access state-of-the-art AI models for image generation, video generation, and LLMs through a unified MCP interface. Fast, scalable, and cost-efficient alternative to traditional AI providers.

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 provides local, private, synchronous access to Ollama models for prompt answering, text classification, and model listing, without any file access or command execution.

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.

Serves an LLM-maintained markdown wiki to agents over MCP, providing tools for querying and navigating wiki pages without direct filesystem access.

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.

Provides AI coding assistants with a persistent Macaulay2 1.26 session, letting them run computations such as Groebner bases, free resolutions, Betti tables, primary decompositions, and Hilbert polynomials while preserving state across calls.

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.