"ollama" matching MCP servers:

MCP server wrapping local Ollama models for offload from API-priced orchestrators. Nine stdio tools - generation, summarisation, analysis, drafting, code tasks (docstring/test/explain/review/types/refactor-suggest), diff-driven tasks (commit-message/pr-description/changelog/summary/impact), mechanical transforms, and model management (list/pull). Apache-2.0.

Enables consulting with local Ollama models for reasoning from alternative viewpoints. Supports sending prompts to Ollama models and listing available models on your local Ollama instance.

Review and rewrite LangChain, LlamaIndex, Ollama, and XRPL code against current APIs, plus runnable examples, import lookup, and XRPL tx skeletons that never submit. Live docs included. $0.001 USDC on Base or 1000 drops XRP.

Self-hosted digests of your Telegram channels over MCP: AI summaries, the last digest and raw per-channel messages. Works with OpenAI, Anthropic or local Ollama.

Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.

Long-term and multimodal memory for AI agents. Store facts and conversations with add_memory, recall them with search_memories — 8 tools over stdio/SSE/HTTP. Per-character memory isolation, LLM-based semantic deduplication, FAISS + JSON storage, and a fully local option (Ollama, no API key). Drop-in compatible with Mem0.

Enables causal root cause analysis with 56 tools covering causal graph construction, 10 RCA model families plus 3 dedicated PyRCA algorithms (Salesforce PyRCA, BSD-3-Clause), multi-model consensus, and PDF/HTML/Excel/Markdown report generation. Works with Claude, Ollama, Groq, OpenAI, Gemini, LangChain, Cursor — 10 providers.

The official Model Context Protocol server for Ambee. It gives any MCP-compatible AI assistant — Claude, ChatGPT, Cursor, VS Code, Ollama, and more direct access to live air quality, pollen, and weather data.

Enables MCP clients like Claude Code and Cursor to use multiple AI models (Gemini, GPT, Grok, DeepSeek, Kimi, Ollama) via a unified chat tool with conversation memory.

Local-first CLI + MCP server for meeting recordings - Whisper transcription,

Judgment calls on small, fast, cheap models: yes/no, pick-one and rating questions about any text, answered YES, NO or UNSURE. Four tools (likely, classify, rate, each) for TypeSafe's Jev, open models on Ollaya, Ollama or a local NLI model.

Real-time cluster health monitoring, pre-request NLMS latency prediction, and intelligent prompt routing across multi-instance LLM backends (vLLM, Ollama, SGLang, TGI).

Enables observability and governance for local LLMs via Ollama, including auditing model usage, scanning prompts for secrets/PII, and enforcing allow/deny policies.

Local-first temporal knowledge graph with six read-only MCP retrieval tools. Supports Ollama and embedded LadybugDB; additions use a separate CLI proposal queue with human approval and explicit application.

Enables generating CAD files through DXF drafting and OpenSCAD operations, with natural-language planning via local Ollama.

Enables AI assistants to control Adobe Photoshop through natural-language requests for tasks like background removal, portrait retouching, web and social export, carousel creation, and batch watermarking. This privacy-focused fork supports a local, free Ollama provider so prompts and images can be processed without an API key or cloud account.

Local-first macOS Markdown workspace MCP server. Run persona mcp so Claude Code / Cursor can read and write notes and tasks; Ollama auto-detect.

A high-performance control plane for Ollama-based local LLM sessions with background memory consolidation, hybrid cloud planning, and real-time fleet monitoring.

Shrinks logs, JSON, docs and web pages before your AI reads them: offline, deterministic, no API key. Folds repetitive log lines (12,037 to 127 tokens on a 400-line log) while code, URLs and quoted strings come back byte-for-byte. Also fetches URLs as clean text, counts tokens exactly, and has optional local Ollama tools for image and text compression.

Exposes local MCP tools for typed, calibrated LLM decisions — gating risky actions, yes/no judging, classification, ordinal rating, and multi-question decisions in one pass. Runs on the model Devin's CLI already provides via ACP (or a fully offline local backend), so agents get calibrated confidence with no extra API key, no Ollama, and no waitlist.