Original): Kalash Vasaniya
Originally published in the direction of artificial intelligence.
LLM bridging for data, tools and services
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MCP (model Context Protocol) quickly becomes a de facto standard for connecting large language models (LLM) with a rich data ecosystem, tools and services they need to be really useful. Instead of a hard review of the API interface into every poem or creating complex “scratchpads”, MCP servers reveal a uniform interface that allows your LLM to discover possibilities, negotiate parameters and performing activities, while maintaining safety, control and continuity of context.
What he does: provides the model reading/saving/creating rights in the sandbox file system so that it can consume local screenshots, output reports or a template of new project structures.
Sandbox enforcement limits the access model only to some folders. File filters (i.e. permission. They are not well designed, delays may occur.
What does it do: it connects LLM with github repositories by gathering browser, search, updates based on differences, generating pulling demands and merging.
Search for code using inquiries in natural language. Priscusing, such as various preview. Multi-Repo orchestration … Read the full blog for free on the medium.
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