Simple MCP Server for Local Sentiment Analysis

The Make A Simple MCP Server project delivers a lightweight, local sentiment‑analysis engine that bridges natural language queries with real‑world data retrieval and automated reporting. At its core, the server interprets user intent from free‑form text, searches relevant news articles via a third‑party search API, performs sentiment scoring on the gathered content, and structures the results into an easily consumable format. Finally, it can dispatch the analysis as a formatted email to stakeholders, enabling rapid insight delivery without manual curation.

For developers building AI assistants that need contextual awareness of current events, this MCP server solves a recurring pain point: how to turn conversational input into actionable data. Instead of hard‑coding search queries or manually parsing results, the server exposes a single MCP endpoint that accepts a natural language prompt. The assistant can then invoke this endpoint, receive a JSON payload containing headlines, sentiment scores, and summary text, and feed that back into the dialogue or downstream workflows. The integration is seamless because the server follows standard MCP conventions for resources, tools, and prompts, allowing it to be plugged into any Claude or other LLM‑powered workflow with minimal configuration.

Key capabilities of the server include:

• Intent parsing – The model automatically interprets what the user wants (e.g., “Show me recent news about AI ethics”) and translates it into a structured search query.
• News retrieval – Leveraging the Serper API, it fetches up to a configurable number of articles that match the query.
• Sentiment analysis – Each article is evaluated for positive, neutral, or negative tone using a pre‑trained sentiment model.
• Structured output – Results are returned as JSON with fields for headline, URL, sentiment score, and a brief excerpt, ready for display or further processing.
• Email automation – The server can send a formatted report via SMTP, enabling automated alerts or daily digests.

Real‑world scenarios that benefit from this MCP server include:

• Media monitoring – Journalists or PR teams can query the latest coverage on a brand or issue and receive instant sentiment reports.
• Market intelligence – Investment analysts can track news trends around specific companies or sectors, automatically flagging negative sentiment spikes.
• Compliance & risk – Compliance officers can monitor regulatory news for emerging risks, with the system summarizing and emailing findings.
• Chatbot enrichment – Conversational agents can answer “What’s the buzz about X?” by delegating to this server, providing up‑to‑date, sentiment‑aware responses.

Because the MCP server is local and lightweight, it sidesteps latency concerns associated with cloud‑only solutions. Developers can run it on a single machine, secure the API key usage, and integrate it into existing AI pipelines without exposing sensitive credentials to external services. Its modular design also means new tools (e.g., different search APIs or sentiment backends) can be swapped in with minimal code changes, giving it a future‑proof edge over monolithic third‑party offerings.