"KLM" matching MCP servers:

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.

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

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.

MCP server that guides LLM security reviews step-by-step, tracking progress and ensuring all assigned source code is read before completing each plan step.

MCP server that provides AI assistants with real-time, current information about AI models from OpenAI, Anthropic, and Google, including pricing, capabilities, and context windows.

Enables image analysis using the GLM-4.6V-Flash model, supporting image URLs and local file paths with custom prompts for tasks like OCR and chart analysis.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

A Model Context Protocol server that routes tasks to Z.ai's GLM-4.7 model, enabling Claude Code to delegate work to a more cost-efficient AI model without sacrificing quality.

A local-first, multi-provider cost meter for LLM usage, exposed as MCP tools. Captures every call into a local SQLite ledger and lets any coding agent query spend, compare providers, and get recommendations — no cloud, no account. First-class support for Chinese providers (Qwen, DeepSeek) alongside Anthropic and OpenAI.

Enables querying and retrieving details of U.S. BLM geothermal leases from the MLRS database, including search and single-lease lookup.

Enables natural language query and ingestion of wiki knowledge bases built from documents, powered by Claude Agent SDK skills.

Enables AI agents to interact with HP ALM / Quality Center for QA workflows including test case management, test execution, defect tracking, and requirements management.

Optimizes token costs by intelligently delegating low-complexity tasks to local LLMs via LiteLLM, enabling cost-effective development workflows.

An MCP server that gives AI agents smart hands for physical machines, controlling them via IP-KVM, BMC, and SSH with visual boot-phase classification and operator-gated actions.

Enables controlling Spotify playback and building LLM-reasoned playlists from any MCP client, reusing an existing spotify_player session with no OAuth.

Implements the Recursive Language Model pattern, enabling LLMs to process arbitrarily long contexts through session-based document management, on-demand chunking, BM25 search, and artifact storage.

Routes your AI tasks to the best available model across 20+ providers — automatically selecting based on task type, budget, and subscription pressure. Supports text, image, video, and audio with built-in cost optimization and fallback chains.

Enables text extraction from images and PDF files using the ZhipuAI GLM-OCR API. It allows users to process documents through local file paths or base64-encoded data for high-quality OCR results.

An MCP server that provides AI agents with a governed wiki requiring human approval before any formal page update, combining structured knowledge management with safe, auditable writes.

Enables AI agents to interact with multiple LLM providers (OpenAI, Anthropic, Google, DeepSeek) through a standardized interface, making it easy to switch between models or use multiple models in the same application.