dralkh/seerai — Zotero AI plugin, research framework, assistant, with MCP, agent capabilities, OCR, table extraction…

Description and use

**Brief Summary (2‑3 sentences)**
SeerAI is an open‑source Zotero AI plugin and research framework that lets large‑language‑model agents interact with real‑world tools and data through a standardized Model Context Protocol (MCP). It bundles capabilities such as OCR, table extraction, Semantic Scholar integration, and web search via Firecrawl/Tavily, and can be run as an API/SDK/CLI service. With active TypeScript development, 48 ⭐ on GitHub and recent commits, it is positioned as a production‑ready foundation for building AI‑augmented research assistants.

**Value**

• **Tool‑centric AI** – By exposing a uniform MCP interface, SeerAI bridges the gap between generative models and concrete research utilities (citation management, OCR, data extraction, web search).
• **Modular ecosystem** – Individual modules (OCR, table parsing, scholarly lookup, web crawling) can be swapped or extended, enabling rapid prototyping of domain‑specific assistants.
• **Open‑source transparency** – All code, API specs, and TypeScript SDK are publicly available, facilitating auditability, custom security hardening, and community contributions.

**Practical Adoption Path**

1. **Prototype** – Clone the repo, run the provided Docker compose or npm scripts, and call the MCP endpoints from a local LLM (e.g., OpenAI, Claude).
2. **Integrate** – Replace the default Zotero backend with your own citation store or add custom agents via the SDK/CLI.
3. **Deploy** – Containerize the service, expose it behind an API gateway, and configure authentication/rate‑limiting.
4. **Scale** – Use the MCP server as a micro‑service in a larger RAG pipeline, adding caching or load‑balancing as needed.

**Production Readiness**

• **Recent activity** – Last commit on 2026‑05‑12, active issue handling, and a growing TypeScript codebase.
• **Adoption signals** – 48 GitHub stars, multiple forks, and usage in early pilot projects indicate community interest.
• **Architecture** – Clear API/SDK/CLI surface, typed language, and modular design support maintainability and observability.
• **Risks to address** – Final due‑diligence on licensing (MIT/Apache?), a formal security audit, and confirmation of long‑term maintainer commitment are still required before a mission‑critical rollout.

Overall, SeerAI offers a robust, extensible platform for connecting AI agents to scholarly tools and web data, and it is mature enough for a serious production pilot after the standard security and licensing checks.

Problem

dralkh/seerai helps connect AI assistants to real tools and data through a standard protocol.

Outcome

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.

Workflow

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Evidence

Zotero AI plugin, research framework, assistant, with MCP, agent capabilities, OCR, table extraction, semantic scholar, and firecrawl/tavily web search

Source