AI automations are only as good as the context they have. You can write the perfect prompt, pick the best model, and build a flawless workflow — but if the AI doesn’t know what your company actually knows, the output is generic at best and hallucinated at worst.
Our knowledge bases with RAG solved this for internal documents. Upload files, import URLs, and JieGou automatically chunks, embeds, and retrieves relevant context at execution time. But most enterprise knowledge doesn’t live in uploaded files. It lives in Confluence wikis, Zendesk help centers, Elasticsearch indices, Pinecone vector stores, Google Drive folders, and dozens of other systems.
Today we’re launching 12 external knowledge source connectors that bring all of that context into JieGou — no custom code required.
The 12 providers
We organized the connectors into four categories based on how they store and surface knowledge:
Enterprise Search
| Provider | What it brings |
|---|---|
| Coveo | AI-powered relevance ranking with answer extraction and citations |
| Elasticsearch | Full-text search with Query DSL across your existing indices |
| Algolia | Real-time faceted search with index-specific queries |
| Glean | Federated company-wide search with people discovery |
These are the systems your team already uses to find information. Now your AI recipes and workflows can search them too — with the same relevance ranking and filtering that humans rely on.
Vector Databases
| Provider | What it brings |
|---|---|
| Pinecone | Semantic search with namespace scoping and metadata filtering |
| Vectara | RAG-as-a-service with built-in hallucination detection and factual consistency scoring |
If you’ve already invested in vector embeddings, these connectors let JieGou query your existing vector stores directly. Vectara’s factual consistency score is particularly useful — it gives every AI response a confidence number that your workflows can use to gate output quality.
Workspace Knowledge
| Provider | What it brings |
|---|---|
| Confluence | CQL search across pages and spaces in your Atlassian wiki |
| Notion | Workspace search across pages and structured database queries |
| Google Drive | Full-text search with Google Workspace document export |
| OneDrive/SharePoint | Microsoft Graph search with file content retrieval |
These are the tools your team writes in every day. Meeting notes, product specs, internal docs, project plans — all searchable by your AI workflows without anyone needing to re-upload anything.
Customer Intelligence
| Provider | What it brings |
|---|---|
| Zendesk | Search across support tickets and Help Center articles with full ticket context |
| Guru | Verified knowledge cards organized in board collections |
Support teams maintain some of the most valuable knowledge in any organization. Zendesk gives your AI access to both ticket history and curated Help Center content. Guru’s verified knowledge cards are especially powerful — they’re already human-reviewed, making them high-quality context for AI grounding.
How it works
1. Connect
Go to Settings > Knowledge Sources, pick a provider, and enter your credentials. Every provider uses API key-based authentication — no OAuth dance required. Credentials are encrypted with AES-256-GCM before storage.
2. Verify
JieGou runs a health check against the provider’s API immediately after you save. You’ll see a green status indicator with response latency, or a clear error message if something is wrong. Health checks run automatically on a schedule so you always know your connections are alive.
3. Use
Once connected, each knowledge source exposes 2-4 MCP tools that are automatically available to your recipes, workflows, and conversational agent. A typical connector provides:
- search — Query the provider’s search API with relevance ranking
- get_document / get_page / get_card — Retrieve a specific item by ID
- list — Browse available collections, indices, or spaces
These tools appear in the MCP tool picker for any recipe or workflow step. You can also scope knowledge sources by department — so Sales sees Salesforce KB context while Support sees Zendesk, all on the same platform.
MCP-native architecture
The key design decision behind knowledge source connectors is that they are MCP tools, not a separate system. Every connector registers its tools through the same Model Context Protocol that powers all of JieGou’s tool integrations.
This means:
- No special API — knowledge tools work identically to any other MCP tool in recipes and workflows
- Automatic availability — connect a source and its tools appear in the tool picker immediately
- Agent-compatible — the conversational agent can search your knowledge sources mid-conversation
- Composable — chain a Confluence search into an Elasticsearch query into a recipe that writes a report
The MCP bridge handles tool registration, credential injection, rate limiting, and audit logging for every call. You connect the source; the framework does the rest.
Enterprise security
Every knowledge source connector includes:
- AES-256-GCM credential encryption — API keys are encrypted at rest and decrypted only at execution time
- Rate limiting — configurable per-source rate limits prevent runaway usage
- Circuit breakers — automatic fail-open when a provider is down, so workflows degrade gracefully
- Audit trail — every tool invocation is logged with timestamp, user, source, and tool name
- Department scoping — restrict which teams can access which knowledge sources
- Health monitoring — latency tracking and automatic status checks
What’s next
Today’s launch covers the 12 most-requested enterprise knowledge systems. The adapter framework is extensible — each new connector is roughly 300 lines of TypeScript following a consistent pattern. We’ll keep growing the provider list based on customer demand.
If you’re already using JieGou’s knowledge bases for internal documents, external connectors complement them perfectly. Internal docs give you curated, high-quality context. External connectors give you breadth — the latest Confluence page, the most recent Zendesk ticket, the freshest vector embeddings — all available to your AI without manual re-uploads.
Availability
External knowledge source connectors are available on Pro plans and above. Starter plans include up to 3 knowledge source connections. Enterprise plans support custom connector development and dedicated infrastructure.