An MCP server for company knowledge is a service that exposes your business's documents, entities, and memory to AI clients over the Model Context Protocol (MCP). When someone asks Claude or ChatGPT a question, the AI calls the server's tools to retrieve the right company context — cited and permission-checked — instead of guessing from its training data.
What MCP is, in one paragraph
MCP — the Model Context Protocol — is an open standard for connecting AI tools to data and actions. It does for AI clients what a USB port did for devices: one protocol, so any compliant client can use any compliant server. An MCP server for company knowledge is simply the server that holds your business's knowledge and answers the AI's questions about it.
What a good one actually does
Serving company knowledge well is more than semantic search over a pile of files. The useful servers do four jobs before the AI ever sees an answer.
- Ingest and structure every document — sync from Notion, Drive, and email, then clean, classify, and embed it.
- Map the business into entities and relationships — people, clients, projects, products — so a question about “WestCape” resolves to the right record.
- Govern retrieval — restricted documents are excluded by sensitivity, every answer is cited, and every call is logged.
- Assemble context — route each question across graph, vectors, and approved memory in one pass, and hand the AI a single context pack.
Build your own, or use a hosted layer?
You can write an MCP server yourself — the protocol is open and the SDKs are good. The question is whether company-knowledge plumbing is where you want to spend your engineering time. Here's the honest trade-off.
| Build your own | A hosted layer (OpsBlox) | |
|---|---|---|
| Time to first answer | Weeks of engineering | The same day you connect a source |
| Connectors | You build and maintain each one | Notion, Drive, email, uploads included |
| Governance | You design permissions, citations, audit | Built in — sensitivity, citations, audit log |
| Graph + memory | Significant extra work | Entity graph + approval-gated memory included |
| Maintenance | Yours forever | Ours — sync, tuning, updates |
| Best when | You have spare engineers and a niche need | You want company knowledge working now |
OpsBlox as your MCP server for company knowledge
OpsBlox is a managed MCP server purpose-built for company knowledge. It exposes twelve tools — retrieval, entity resolution, graph lookups, and an approval-gated memory — over a TypeScript service backed by Postgres and pgvector. You connect your sources; your team's AI gets governed, cited context with one config entry.
Common questions
Is an MCP server the same as a chatbot?+
No. An MCP server has no chat interface of its own — it's infrastructure that sits under the AI clients your team already uses (Claude, ChatGPT, Cursor) and feeds them context. You keep your existing AI; the server makes it accurate about your business.
Which clients can connect to an MCP server for company knowledge?+
Any MCP-capable client. Claude Desktop and Claude Code work today; ChatGPT, Cursor and others connect the same way as they ship MCP support — there's no per-client integration to build.
Where does the company data live?+
With OpsBlox, in an isolated tenancy hosted in South Africa (AWS Cape Town), or entirely on an on-prem box inside your own network. Data is encrypted at rest and never used to train a model.