tech
December 3, 2025
Agentic Workflow with Jina Remote MCP Server
We showed you, in a previous post, how to integrate Jina AI’s search and reader APIs with DeepSeek R1 to build a deep research agent, but it took a lot of custom code and prompt engineering to make it work. In this post we’ll do the same thing using the Model Context Protocol (MCP), which uses a lot less custom code and is portable to different LLMs, but is still subject to a few pitfalls along the way.
TL;DR
- Jina MCP simplifies agent development by integrating APIs with LLMs, reducing custom code and enhancing reliability.
- MCP acts as a universal plugin system, allowing agents to chain tools and data sources for planning, reasoning, and action.
- The Jina MCP server provides access to various tools including web scraping, search, image search, and document reranking.
- Example agents demonstrate capabilities in academic paper summarization, competitive intelligence reporting, and AI legal compliance analysis.
- While LLMs can be a bottleneck, MCP facilitates reliable multi-step task execution without custom code.
- The MCP ecosystem is expanding, making robust agent implementations more accessible for practical applications.
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