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README.md

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@@ -110,6 +110,8 @@ A growing set of community-developed and maintained servers demonstrates various
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- **[Atlassian](https://github.com/sooperset/mcp-atlassian)** - Interact with Atlassian Cloud products (Confluence and Jira) including searching/reading Confluence spaces/pages, accessing Jira issues, and project metadata.
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- **[Google Tasks](https://github.com/zcaceres/gtasks-mcp)** - Google Tasks API Model Context Protocol Server.
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- **[Fetch](https://github.com/zcaceres/fetch-mcp)** - A server that flexibly fetches HTML, JSON, Markdown, or plaintext
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- **[AWS S3](https://github.com/aws-samples/sample-mcp-server-s3)** - A sample MCP server for AWS S3 that flexibly fetches objects from S3 such as PDF documents
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- **[Elasticsearch](https://github.com/cr7258/elasticsearch-mcp-server)** - MCP server implementation that provides Elasticsearch interaction.
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- **[Cloudinary](https://github.com/felores/cloudinary-mcp-server)** - Cloudinary Model Context Protocol Server to upload media to Cloudinary and get back the media link and details.
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## 📚 Frameworks

src/everything/everything.ts

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@@ -411,7 +411,7 @@ export const createServer = () => {
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maxTokens,
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);
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return {
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content: [{ type: "text", text: `LLM sampling result: ${result}` }],
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content: [{ type: "text", text: `LLM sampling result: ${result.content.text}` }],
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};
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}
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