"ONNX" matching MCP servers:

Local RAG system for Claude Code with hybrid search (semantic + BM25), cross-encoder reranking, markdown-aware chunking, and 12 MCP tools. Zero external servers, pure ONNX in-process.

Local semantic recall MCP server for citation-integrity workflows. Enables semantic search over a text corpus, returning file paths and page numbers for verification, with 100% local processing using ONNX embeddings and LanceDB.

Local-first dev memory: indexes Git commits, PRs, Jira/Linear tickets, Confluence docs, Slack threads, and Calendar events into a local SQLite/FTS5/ONNX index, and exposes them as MCP tools so Claude Code, Cursor, and Codex can search and cite your past work.

Semantix-Verify is an MCP server for semantic validation of AI/LLM outputs. It exposes a single tool, verify_text_intent(text, intent_description, threshold), which uses a local quantized NLI cross-encoder (INT8 ONNX) to return a 0.0–1.0 probability that the text satisfies the given intent — and, when it doesn't, a structured correction prompt for agent retry loops. Useful for building com

Knowledge graph for token-efficient code reviews. Builds a structural map of your codebase with Tree-sitter, tracks changes incrementally, and gives AI agents precise context via MCP tools. Features fixed multi-word search, qualified call resolution, dual-mode embedding (ONNX local + LiteLLM cloud), and output pagination.

Semantic vector DB as an MCP server for Claude Code — SQLite + FTS5 + local ONNX embeddings. Gives Claude persistent, searchable project knowledge across conversations.

The open retrieval layer for AI agents. Index your entire project — code, docs, legal, research, data — and serve surgical context via MCP. FTS5 full-text search, optional semantic search (FastEmbed/ONNX), 10 built-in parsers, incremental auto-sync.

Local-first code intelligence MCP server with hybrid BM25 + ONNX vector search, symbol-level impact analysis, diff-aware PR review with risk scoring, and persistent memory tied to git state.

A drop-in replacement for Anthropic's memory server that utilizes SQLite to ensure data integrity and concurrent access. It enhances the original functionality with semantic search capabilities using vector embeddings and ONNX models.

Provides persistent knowledge graph memory for AI agents with local semantic search using Neo4j and ONNX embeddings, enabling offline operation with zero API costs.

Provides AI systems with access to Onyx programming language documentation through web crawling and intelligent search capabilities.

Connect your MCP-compatible clients to Onyx AI knowledge bases for enhanced semantic search and chat capabilities. Retrieve relevant context from your documents seamlessly, enabling powerful interactions and comprehensive answers. Streamline knowledge management and improve access to information acr

Local-first markdown vault with a built-in MCP server (streamable HTTP). 16 tools and 2 resources for Claude Code / Desktop / Cursor: read/write/search plus context_for_query, find_orphans, weekly_digest, compare_notes, semantic_outline. Per-folder agent permissions, LanceDB vectors, local Xenova ONNX embedder swappable to Ollama. Single Bun binary. AGPL.

Semantic memory server for AI agent teams. Stores, searches, and retrieves knowledge across sessions using pluggable vector backends with local ONNX embeddings, exposed as an MCP server.

Build a paid MCP server that charges AI agents per call in USDC, with automatic payment handling via HTTP 402 and EIP-3009.

Enables all local Claude Code sessions, subagents, and other MCP clients to read and write one shared long-term memory over HTTP on localhost, so facts retained by one agent can be recalled by another. It extracts atomic facts, entities, and observations into an embedded local Postgres with ONNX embeddings and reranking, requiring no API key.

Local MCP server that gives AI agents 44 engine tools to build, run, and debug real 2D and 3D games through conversation.

Local MCP server for neural text-to-speech using Kokoro ONNX engine on CPU, supporting SSML tags, multiple voice profiles, and zero-GPU operation for low-latency speech synthesis.

Enables inspecting ONNX models, probing the deployment environment, and benchmarking inference latency and FPS either locally or on remote SSH targets such as Linux workstations and Jetson devices. Benchmark results are validated against FPS, P95 latency and model-size constraints to produce PASS/FAIL deployment gates.

Enables local candidate review of ONNX or TFLite models by checking static evidence and externally measured results against a fixed policy, producing accept/reject/hold evidence ZIPs for AI agent workflows.