A unified agent memory workspace for human and agent | 一个统一的agent记忆工作空间

Run AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating

Telegram for your terminal and your AI agents: read, search, send and press bot buttons on your own account. MCP server included.

Web search and content extraction with Tavily and Exa via inference.sh CLI. Apps: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract. Capabilities: AI-powered search, content extraction, direct answers, research. Use for: research, RAG pipelines, fact-checking, content aggregation, a

Run AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating

Claude Code skill that forces AI to understand before executing. Three disciplines: cognition check, requirement understanding, method search.

Automated harness evolution for AI agents. A Claude Code plugin that iteratively optimizes system prompts, routing, retrieval, and orchestration code using full-trace counterfactual diagnosis. Based on Meta-Harness (Lee et al., 2026).

Structural memory for AI coding agents. Bi-temporal graph, MCP-native, zero LLM calls. Cursor · Claude Code · Codex · DeepSeek Harness · Hermes · VS Code · Windsurf.

Turn DeepSeek Harness into a self-hosted enterprise Agent platform with knowledge, deep research, content generation, vibe coding, browser automation, governance, and admin controls.

The most advanced, fully offline client-side AI suite on Android today.

Persistent visual cache for LLM-driven software development. Caches screenshots using perceptual hashing, vector search, and AX trees to prevent token overhead and visual hallucination loops.

Code intelligence for agents: find the code that matters and keep your context window and tokens lean.

Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus.

Persistent project knowledge graph for coding agents. MCP server with semantic search, in-process embeddings, and web explorer.

Enables AI coding agents to retrieve compact structural codebase context through repository architecture summaries, AST symbol extraction, cyclomatic complexity scoring, and TODO/FIXME hotspot search.

Enables Google Gemini to autonomously read, write, search, and patch code files and run whitelisted developer commands inside a sandboxed local workspace for edit-and-verify coding workflows.

Enables MCP clients to search and read Notability notes, including handwritten pages via OCR-based fuzzy search and page images rendered as PNGs. Runs entirely against a local synced index, so queries never touch the network.

Enables AI clients to search Korean court auction real estate by court, region, usage, sale date, appraisal/minimum price, and failure count; fetch case details; collect and resume jobs; and export results to Excel, CSV, and JSONL.

A stdio MCP server that lets AI coding assistants search, read, add, and review shared markdown notes in a team git repository, including teammate knowledge and recent work, without extra AI calls.

Enables Claude and other MCP clients to search finn.no and create, manage, and publish Torget ads from photos — preparing images (EXIF/GPS stripping, resize, HEIC), writing titles and Norwegian descriptions, suggesting category and market price, checking for duplicates, and publishing only after explicit confirmation. Read-only search, listing details, saved-search diffs, and management of your own ads are also supported through a locally stored logged-in session.

Enables MCP clients to inspect PDF structure and extract object-level data such as characters, words, tables, images, fonts, and metadata, with JSON/CSV export and image retrieval.

Enables any MCP-compatible client to persist long-term memories for AI agents, with LLM-based fact extraction, semantic vector search, update/delete/list operations, and queue status checks across sessions.

Enables MCP-compatible AI clients to search and view CRM customers, deals, contracts, tasks, calendars, and outbound jobs, and to propose opt-in write actions that require human approval in the CRM.

Enables MCP clients such as Claude to search, tag, catalogue, ingest, audit, relocate, and repair a running Connecter asset library, including texture scanning and relinking, with dry-run plans and undoable journaled changes.