elgorro/aiquila — Connect Claude AI to your Nextcloud via the Model Context Protocol.

Description and use

**Brief Summary (2‑3 sentences)**
elgorro/aiquila is an open‑source TypeScript server that implements the Model Context Protocol (MCP), enabling Claude‑style AI assistants to interact with a Nextcloud instance via natural‑language commands. It lets users browse, search, and manage files in Nextcloud through conversational queries, turning the storage platform into a live knowledge base for AI agents. The project is actively maintained, with recent commits and a growing community, making it a solid candidate for pilot deployments.

**Value Proposition**

• **Standardized AI‑to‑tool bridge:** By adhering to MCP, aiquila provides a vendor‑agnostic way to expose real‑world data and actions to any compliant LLM, reducing the need for custom integration code.
• **Immediate productivity gains:** Users can retrieve, organize, and modify Nextcloud files simply by asking the AI, accelerating workflows such as document discovery, project hand‑offs, and collaborative editing.
• **Reusable building block:** Teams can ship their own MCP servers or extend aiquila to other services, creating a consistent integration layer across the organization’s toolchain.

**Practical Adoption Path**

1. **Prototype:** Deploy the Docker image or run the TypeScript source in a sandboxed environment and point it at a test Nextcloud instance. Use the provided CLI or SDK to issue simple “list files” or “search” queries and verify response formats.
2. **Integration:** Connect Claude (or any MCP‑compatible LLM) to the aiquila endpoint via the MCP client libraries. Define the conversation intents (e.g., list_documents, download_file) and map them to aiquila’s API calls.
3. **Security hardening:** Enable Nextcloud OAuth/App passwords, restrict the aiquila service to your internal network, and audit the generated API tokens.
4. **Scale:** Deploy the service behind a load balancer, enable TLS, and configure caching or rate‑limiting if the AI will be handling high query volumes.
5. **Extend:** Fork the repo to add custom actions (e.g., file versioning, sharing links) or to support additional Nextcloud plugins, then push the changes back to the community if useful.

**Production Readiness**

• **Activity & community:** 21 stars, 3 forks, last commit on 2026‑06‑27, and a clear TypeScript codebase with an SDK/CLI indicate healthy momentum.
• **Maturity of core features:** Core MCP endpoints (browse, search, file CRUD) are implemented and documented, making the “read‑only” use case production‑ready today.
• **Operational considerations:** The service runs as a lightweight Node.js process; containerization is straightforward, and typical DevOps tooling (CI/CD, monitoring) can be applied without special requirements.
• **Risks to address before full rollout:** Verify the open‑source license compatibility with your stack, conduct a security audit of the Nextcloud token handling, and confirm that maintainers are responsive to issues. Once these checks are completed, aiquila can be considered production‑grade for pilot projects and, with proper hardening, for broader enterprise deployment.

Problem

elgorro/aiquila 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

Connect Claude AI to your Nextcloud via the Model Context Protocol. Browse, search, and manage files through natural conversation.

Source