Your documentation, askable by EVERY AI
Every Smart Documentation set comes with its own MCP endpoint, so your AI assistants and chatbots answer from the same current product knowledge.
We answer from the documentation, not the whole CODEBASE
A raw codebase contains enormous amounts of implementation detail. Most user questions only need a small, relevant part of that context.
Ask an LLM directly on the codebase
The model has to reconstruct the answer from raw technical context each time.
- Large repositories can require a lot of context and therefore more tokens
- Implementation detail is mixed with the information the user actually needs
- The model has to reason out the product flow again for every question
- Repeated questions can still produce differently phrased or differently scoped answers
- Audience, terminology and documentation structure have to be recreated in the prompt
Ask through a Smartdoxx MCP
The model starts from product knowledge that has already been detected, structured and documented.
- Focused documentation can reduce how much context needs to be retrieved
- The relevant flows are already translated into human-readable knowledge
- Each MCP has a defined documentation scope and audience
- Repeated questions are grounded in the same structured source
- The source updates when the underlying product documentation updates
Every documentation set gets its own MCP
The MCP is not another knowledge base to maintain. It is an access layer on top of the documentation Smartdoxx already generates from your product knowledge.
Your codebase
The implementation remains the source of truth.
Smartdoxx knowledge layer
UI, AI, automated and CLI flows are detected and turned into reusable product knowledge.
Your documentation + MCPs
Each documentation set can expose its own focused MCP endpoint.
We retrieve the context your question ACTUALLY NEEDS
Instead of asking one assistant to understand everything for everyone, each documentation and MCP can represent the context that a specific audience actually needs.
Right scope
An end-user MCP does not need the same level of detail as technical onboarding. The assistant can work from the documentation designed for that audience.
Right terminology
The documentation already contains the structure, wording and level of detail you chose, so the assistant has a stronger base for concise answers.
Right source
The answer is grounded in documentation that is downstream from the Smartdoxx knowledge layer and kept aligned with product changes.
Your team asks where they already WORK
The endpoint can sit behind the AI assistant or workflow where the question is already being asked.
“What steps does the customer need to complete before we can activate this integration?”
Customer Success MCP“Which configuration steps are required before the first synchronization can run?”
Partner MCP“What is the functional flow when a user approves this request?”
Functional docs MCP“Which components participate in this automated flow and where does it start?”
Technical MCPSame source. Same scope. More REPEATABLE answers
Language models can still phrase answers differently. The advantage is that Smartdoxx gives repeated questions a stable information boundary: the same documentation scope, the same product knowledge and the same maintained source.
Less re-discovery
The model does not have to rediscover the full functional meaning of the codebase before it can answer a product question.
Less unnecessary context
Focused retrieval can avoid repeatedly sending broad repository context when only a specific documented flow is relevant.
Less knowledge drift
Docs and MCP answers sit on the same knowledge layer, so there is less room for a chatbot knowledge base to evolve separately from your documentation.
Make every documentation set ASKABLE
Generate the knowledge once, structure it for the right audience, keep it aligned with the product and expose it through its own MCP whenever your users or teams need a short answer.