Implement multi-tenant architecture for Vectra AI MCP Server#5
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yashk0thari wants to merge 2 commits intovectra-ai-research:mainfrom
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Implement multi-tenant architecture for Vectra AI MCP Server#5yashk0thari wants to merge 2 commits intovectra-ai-research:mainfrom
yashk0thari wants to merge 2 commits intovectra-ai-research:mainfrom
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…ti-Tenant Converter - Introduced detailed implementation guide (IMPLEMENTATION.md) outlining the phases for converting single-tenant MCP servers to multi-tenant architecture. - Created README.md to provide an overview, quick start instructions, features, and usage examples for the MCP Multi-Tenant Converter skill. - Added skill.md to describe the skill's functionality, phases, and interactive workflow for users. - Updated documentation to reflect the minimal footprint approach for application-level patching, ensuring only necessary modifications are made. - Included templates for middleware and runner to facilitate the conversion process.
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- Introduced Kindo framework to support multi-tenant functionality, allowing a single server instance to handle multiple tenants with isolated credentials. - Created new files for middleware, runner, and tests, enhancing the overall structure and maintainability of the project. - Modified `server.py` to integrate Kindo patches and maintain backward compatibility with single-tenant mode. - Added comprehensive documentation including migration guide, quick start instructions, and detailed architecture overview. - Implemented a robust test suite to ensure functionality and reliability of the new multi-tenant features.
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kindo/middleware/credentials.py,kindo/runner.py, and comprehensive tests.server.pyto support dual-mode operation (single-tenant and multi-tenant).MIGRATION.mdandMULTI_TENANT_README.md.