Your employees spend 1.8 hours per day searching for internal information. 35 percent of those searches fail completely. A Company Docs MCP server makes every answer findable in 12 seconds with 96 percent accuracy.
Your SOPs are in Google Docs. Your product specs are in Notion. Your engineering wiki is in Confluence. Your HR handbook is a PDF nobody has opened since onboarding. When someone needs to know the refund policy, the deployment process, or the brand voice guidelines, they either search for 20 minutes or ping a colleague on Slack and wait for a response.
You have tried putting everything in one place before. It lasted two weeks before the documentation diverged again. The problem is not organization. It is access. You need a system that reads documentation wherever it lives and surfaces the right answer instantly.
system cost
manual cost replaced
cost reduction
The stack
The Company Docs MCP server creates a unified search layer on top of all your documentation without requiring you to move or reorganize anything.
Setup has 3 phases. Phase 1 (Indexing): The MCP server connects to your documentation sources (Google Drive, Notion, Confluence, local markdown files, PDFs) and creates a vector index of every document. Phase 2 (Chunking): Documents are split into semantically meaningful chunks with metadata: source URL, last updated date, author, and category.
Phase 3 (Querying): When you or an employee asks Claude a question, the MCP server retrieves the most relevant chunks from the index and injects them into Claude's context. Claude answers using only the retrieved documentation and cites the specific source for every claim. If the answer is not in the docs, it says so instead of guessing.
Runs locally or on a server, connects to your documentation platforms via API, maintains the vector index, and responds to Claude's search queries with relevant document chunks.
Phase 1 indexes your Google Drive so every SOP and shared doc becomes searchable in place, no migration required.
The Notion connector pulls in product specs and wikis, chunked with their source URL and last-updated date so citations stay accurate.
Indexes your Confluence spaces so the engineering wiki answers questions directly instead of sitting behind a 20-minute search.
Receives the retrieved document chunks as context and generates human-readable answers with source citations. Operates under strict rules: only answer from provided context, never fabricate information.
Provides a Slack bot or web interface where any team member can ask questions without needing Claude Desktop. Routes questions to the MCP-connected Claude instance and returns answers in the channel.
What it replaces
2 line items, starting with the knowledge manager, priced against the tools that now do the work. The last bar is the whole system at $30/mo.
Knowledge Manager, now Company Docs MCP
Employee search time, now 12-second answers
The whole system
Monthly cost of each role the system replaces, against the system itself.
Why it holds
Everyone can buy MCP. What separates the setups that last from the ones that collapse is one idea.
The difference between a useful internal knowledge bot and a useless one is citation. When Claude answers with 'According to your Refund Policy document (last updated March 2026), the standard refund window is 30 days,' employees trust it. When it answers with 'The refund window is probably 30 days,' they do not. Always force citation. It is the single biggest factor in adoption.
What is inside
This is not theory. 3 pieces, ready to run.
In this playbook
2 of 3How it's built
The file tree, so you know exactly what you would be standing up.
- indexer/
- gdrive_connector.tsnotion_connector.tsconfluence_connector.tspdf_parser.js
- server/
- mcp_server.tsvector_store.jschunk_retriever.tscitation_builder.js
One rule to leave with, the one that stops the knowledge manager from creeping back into the budget.
Your company documentation already has the answers. Your team just cannot find them. Fix the access layer and 1.8 hours per day comes back.
The numbers above trace back to the Enterprise Knowledge Search Study, not projections.
You can wire MCP and the rest of this stack by hand from the playbook above. Or you skip the assembly, because standing up systems like this is exactly what Ultron does.
is what this system replaces every month. Ultron runs it for $30/mo.
No card required. Set it up in about ten minutes.