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Merge branch 'main' into patch-1

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Justin Spahr-Summers 2025-01-10 12:44:42 +00:00 • committed by GitHub
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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
- **[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. - **[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.
- **[Google Tasks](https://github.com/zcaceres/gtasks-mcp)** - Google Tasks API Model Context Protocol Server. - **[Google Tasks](https://github.com/zcaceres/gtasks-mcp)** - Google Tasks API Model Context Protocol Server.
- **[Fetch](https://github.com/zcaceres/fetch-mcp)** - A server that flexibly fetches HTML, JSON, Markdown, or plaintext - **[Fetch](https://github.com/zcaceres/fetch-mcp)** - A server that flexibly fetches HTML, JSON, Markdown, or plaintext
- **[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
- **[Elasticsearch](https://github.com/cr7258/elasticsearch-mcp-server)** - MCP server implementation that provides Elasticsearch interaction.
- **[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. - **[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.
## 📚 Frameworks ## 📚 Frameworks

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