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Integrate New LLM Providers with DeepChat AI Agent Skill

Integrate New LLM Providers with DeepChat AI Agent Skill

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Works withClaude CodeCursorCodexGemini CLI
Integrate New LLM Providers with DeepChat AI Agent Skill

Integrate New LLM Providers with DeepChat AI Agent Skill

Regular price £21.99
Regular price £21.99 Sale price
SAVE Sold out

Integrate New LLM Providers with DeepChat AI Agent Skill

The "Integrate New LLM Providers with DeepChat AI Agent Skill" enables developers to extend the capabilities of DeepChat by adding new large language model (LLM) providers through deliberate modifications to the source code. This skill is tailored for cases where developers need to introduce a provider, its profile, configuration, model mapping, authentication behavior, or specific adapter within the DeepChat architecture.

What this skill does

This skill involves the insertion of a new DeepChat LLM provider by making structured changes to the source repository. Developers will:

  • Identify and assign a unique Provider ID in kebab case.
  • Specify display name, API type, and known transport family.
  • Configure default base URL and authentication type (e.g., API key, OAuth).
  • Establish model metadata source and test model parameters.
  • Account for any API request quirks such as headers, endpoint suffixes, or tool-call support.
  • Implement changes in necessary files, including `defaults.ts`, `providerId.ts`, and `providerRegistry.ts`.

Who it is for

This skill is primarily designed for developers and development teams utilizing AI coding agents like Claude Code, Cursor, or Codex. It is particularly beneficial for those seeking to customize and enhance the LLM provider selection within their DeepChat deployment.

Use cases

  • Adding a new LLM provider to support specialized AI tasks not covered by existing options.
  • Integrating a proprietary LLM service to seamlessly interact with the DeepChat ecosystem.
  • Customizing provider configurations to align with unique project requirements and organizational standards.

Technical details

This skill requires integration through direct source code modifications, guided by the existing provider architecture in DeepChat. It supports the addition of OpenAI-Compatible APIs when applicable, and involves changes to provider configuration files to facilitate seamless integration. This includes working with files such as `src/main/provider/defaults.ts`, `src/main/provider/providerId.ts`, and `src/shared/providerDbCatalog.ts` depending on the model source requirements.


Source & Licence

This package is built on open-source work published by ThinkInAIXYZ (ThinkInAIXYZ/deepchat) and distributed under Apache-2.0. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted under the Apache License 2.0, which also includes an express patent grant. Attribution and any NOTICE file must be retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

  • Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
  • Format: ZIP archive containing the skill files, documentation and the original licence.
  • Support: support@mcpcart.com — we aim to reply within 2 business days.
  • Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.

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