Best for
- TypeScript teams needing a unified API across multiple AI providers
- Applications requiring MCP integration, RAG, memory, or provider failover
- Developers who want both an SDK and a professional CLI
N
46FMRS · D
NeuroLink is a broad Juspay AI integration platform in which MCP is one connectivity and tool-management capability. Because the source lacks a cached server manifest, it should not be presented as an independently verified MCP server with a complete tool list or transport declaration.
NeuroLink is a TypeScript-first AI integration platform extracted from Juspay production systems. It provides one API for 30+ AI providers and 100+ models, with streaming, MCP server connectivity, voice, RAG, memory, multimodal file processing, provider failover, and a CLI. The source does not provide a standalone MCP server manifest, so its independently exposed MCP tools and transport cannot be verified.
Tools
getCurrentTime
Provides access to the current time.
readFile
Reads file contents.
writeFile
Writes file contents.
listDirectory
Lists directory contents.
calculateMath
Performs mathematical operations.
websearchGrounding
Provides Google Vertex web search and requires credentials.
Setup
Install @juspay/neurolink with npm, pnpm, or yarn, or run the CLI with npx. Configure at least one AI provider API key through the setup wizard or environment variables. When connecting external MCP servers, configure the required command or URL, transport, and credentials for each server.
Fit and risk
Not for
- Users seeking a standalone MCP server with a verified tool manifest and transport
- Users unwilling to configure AI provider credentials
- Simple MCP use cases that do not need a TypeScript SDK, CLI, or multi-provider features
Required permissions
- API credentials for configured AI providers
- Appropriate local file read permissions when processing files
- File write permissions when using the built-in writeFile tool
- Tokens, environment variables, or authorization required by connected external MCP servers
- ffmpeg or bundled ffmpeg-static may be required for video processing
Risks and side effects
- Prompts, files, or audio may be sent to the selected AI provider; data handling depends on provider configuration
- writeFile and external MCP tools may modify data or trigger external actions
- Invalid credentials, rate limits, or provider outages can cause requests to fail
- Tokens and permission scopes for external MCP servers affect the security boundary
- Audio, video, and large-context processing may require additional dependencies or resources
Troubleshooting
- Run setup or confirm that at least one provider API key is configured
- Check that provider and model names match the configured credentials
- For rate limits or outages, configure multiple providers or use fallback/modelChain
- For video failures, check that ffmpeg is available
- For Redis memory, verify REDIS_URL, connection settings, and Redis availability
- For external MCP connections, verify the command, URL, transport, headers, environment variables, and retry settings
Use cases
Switching between AI providers without rewriting application code
Building AI applications with streaming, RAG, memory, and multimodal file processing
Connecting external MCP servers such as GitHub, Slack, and PostgreSQL
Running generation, evaluation, RAG, and interactive sessions through the CLI
Building TTS, STT, or realtime voice applications
Supported clients
Supported clients have not been confirmed yet.