The Best MCP Gateway Options for Confluence MCP Server
Confluence started as a wiki. Today it’s where organizational knowledge lives, and the Atlassian remote MCP server gives AI agents direct access to that knowledge base.
The use cases are immediate: an agent that can search and surface the right Confluence page rather than making someone hunt through spaces manually. Using a Confluence integration with your AI agent is also easy to implement because Atlassian hosts their remote MCP server on their infrastructure, meaning you can connect to it over the network. That makes setup straightforward, but it also means AI agents are being pointed at a cloud endpoint that can reach your entire Confluence instance.
Sensitive HR policies sit in the same system as public engineering docs. Executive strategy pages sit alongside team wikis. The access control and governance questions that creates are exactly why a gateway matters. A gateway also addresses some specific production pain points that Confluence users have been hitting in practice.
This guide covers the best MCP gateway options for teams running the Confluence MCP server, and how to choose the right one.
Why You Need an MCP Gateway for the Confluence MCP Server
Connecting agents directly to the Confluence MCP server without a control layer works for a prototype. For organizational use, where Confluence holds sensitive documentation across every function in the business, the gaps become serious quickly.
OAuth Expiration Issues
Atlassian’s OAuth tokens expire on a short cycle, and the Confluence integration uses this server, inhering this issue. MCP clients aren’t built to handle Atlassian’s specific expiry window , and the result is sessions that drop mid-workflow, requiring manual re-authentication. For tools running unattended, like automation pipelines that surface documentation on a schedule, there’s no mechanism to re-authenticate at all. The workflow simply stops.
A gateway resolves this by owning the Atlassian session and refreshing tokens before they expire — invisibly, at the infrastructure layer, without interrupting whatever the agent is doing.
Sensitive Content Requires Scoped Access
Confluence holds information that isn’t meant for every agent or every user. HR documentation, legal policies, executive planning pages, financial records live alongside engineering wikis and public team spaces in the same Confluence instance. Without a gateway enforcing access controls, every connected agent can reach all of it.
A gateway lets you define exactly what each agent can access.
No Record of What Agents Are Accessing
Confluence contains documentation that carries compliance and legal weight (e.g., policies, procedures, audit records, contractual documentation). When AI agents are reading and writing that content, you need a record of what happened. Without a gateway, there’s no centralized log of agent activity in Confluence. A gateway provides per-call audit trails: which agent accessed which page, when, with what result.
Documentation Retrieval Overwhelms Context Windows
Confluence pages can be long. When an agent retrieves documentation to answer a question or provide context, it may pull far more content than the model can usefully process — especially when searching across multiple spaces. A gateway with payload filtering controls what gets passed to the model, preventing context overload and keeping documentation retrieval workflows functional.
Governing Knowledge Access at Organizational Scale
When Confluence MCP usage spreads across teams, the governance questions multiply. Which agents can write to which spaces? Who approved an agent’s access to a sensitive policy document? Can IT see what’s happening across the organization? Without a gateway, none of these questions have good answers. A gateway provides the centralized control point for policies, permissions, and logs that make organizational-scale Confluence MCP manageable.
MCP Manager by Usercentrics: Easiest MCP Gateway for Scalable AI Governance
MCP Manager is purpose-built for enterprise MCP governance, and it’s created by a team that has built popular Atlassian Marketplace apps. You can also find MCP Manager in the Atlassian Marketplace, making it a natural fit for organizations already running Confluence as part of their Atlassian stack.
For teams using the Confluence MCP server in production, MCP Manager addresses the core challenges:
- Session management: MCP Manager owns the Atlassian OAuth connection, refreshing tokens proactively so agents never hit an expired session mid-workflow. The token expiry problem becomes invisible to clients.
- Space and page-level access control: Define which agents can access which Confluence spaces, which tools they can invoke, and whether they have read or write permissions — without modifying agent configurations.
- Payload filtering: Control what Confluence content gets passed to your model, preventing long pages or large search results from overwhelming context windows during documentation retrieval workflows.
- Full audit logging: Every Confluence tool call recorded with agent identity, tool name, parameters, and result — essential for compliance in organizations where documentation carries legal or regulatory weight.
- PII and sensitive data protection: Catch personally identifiable information and sensitive content before it reaches your models, particularly important when agents are traversing HR or legal spaces.
- Org-wide visibility: A single dashboard showing all Confluence MCP activity across every team and agent in your organization.
MCP Manager is built by the team behind Visor, one of the most widely used apps in the Atlassian Marketplace. That background gives the team direct familiarity with how Atlassian’s infrastructure behaves in enterprise environments at scale. You can find MCP Manager in the Atlassian Marketplace, or start a free trial at mcpmanager.ai.
Kong AI Gateway: Worth Considering If You’re Already on Kong’s Platform
Kong’s AI Gateway extends their established API management platform to support MCP. For organizations where Kong already handles routing and authentication across their API surface, adding Confluence MCP traffic through the same platform reduces net-new tooling overhead.
The honest limitation for Confluence specifically: MCP connections are stateful in ways that traditional API management wasn’t designed for. Handling Atlassian’s token refresh behavior and the multi-turn nature of documentation retrieval workflows requires custom configuration that teams not already invested in Kong will find difficult to justify. If Kong isn’t already part of your infrastructure, purpose-built alternatives are a more direct path.
Amazon Bedrock AgentCore: Worth Considering If You’re Building on AWS
AgentCore is Amazon’s managed agent infrastructure platform, with MCP gateway functionality built into a broader stack that includes serverless compute and native AWS service integration. For organizations running AI workloads on Bedrock, connecting to the Confluence MCP server through AgentCore fits naturally into existing AWS infrastructure — IAM authorization, CloudWatch logging, and CloudTrail audit trails come along without additional configuration.
The constraint is platform commitment. AgentCore’s Confluence MCP integration isn’t something you add to an existing setup — it’s part of building on Bedrock. Organizations using Confluence across teams that also rely on non-AWS tooling will hit integration friction. If you’re evaluating gateways as a standalone decision, there are more focused options.
TrueFoundry: Best for Teams Wanting a Full AI Platform
TrueFoundry is a full AI and agent platform with MCP gateway functionality built in. For teams building Confluence-connected agents from scratch and wanting a unified environment for model access, deployment, and tooling, TrueFoundry keeps the stack consolidated; LLMs and MCP tools managed together rather than across separate products.
For Confluence specifically, TrueFoundry gives developers a single platform to build and deploy agents that search documentation, surface knowledge across spaces, and write content back to Confluence pages — without managing separate infrastructure for model routing and MCP connectivity.
The caveats are worth understanding before committing. TrueFoundry is built for engineering teams writing agents in code — the feature set reflects that audience rather than IT governance or compliance teams. Organizations that need production-grade RBAC across Confluence spaces, compliance audit trails, or controls that satisfy a security review will find the governance layer thinner than purpose-built alternatives. MCP support is also still maturing on the platform, so verifying current feature depth against your requirements before committing is worthwhile.
Building Your Own: Why Most Organizations Regret It
A custom proxy layer between your agents and the Confluence MCP server is technically buildable. Some organizations attempt it when their requirements seem unusual enough to justify the effort.
What that actually means in practice: owning the Atlassian OAuth implementation, including token refresh logic and the edge cases that vary between client types. Building observability from scratch. Implementing space-level and page-level access controls. Keeping up with MCP protocol changes. Managing secrets securely across every team using Confluence through agents.
The maintenance burden compounds faster than most teams expect. By the time a custom gateway replicates the core capabilities of a purpose-built solution, the engineering investment is hard to justify against what was available off the shelf. Build your own if your requirements genuinely can’t be met any other way — for most Confluence deployments, that threshold is rarely reached.
Choosing the Right MCP Gateway for Your Confluence Integration
| Your situation | What matters most | Best fit |
|---|---|---|
| Multiple teams using Confluence, compliance or IT oversight required | Space-level RBAC, audit trails, token management, PII detection | MCP Manager by Usercentrics |
| Already standardized on Kong | Platform consolidation, existing operational patterns | Kong AI Gateway |
| AWS-native AI infrastructure | Serverless, IAM integration, CloudTrail logging | Amazon Bedrock AgentCore |
| Building agents in code, want a unified AI platform | Model + tool management in one place | TrueFoundry |
| Genuinely unique requirements | Complete control over implementation | Build your own (with caution) |
Confluence’s role as an organizational knowledge layer is what makes the gateway decision consequential. The more teams relying on Confluence to store sensitive, compliance-relevant, or strategically important documentation, the more important it is to control how AI agents interact with it.
See It in Action: Atlassian MCP Gateway Demo
The video below shows MCP Manager running a secure multi-server Claude setup using the Atlassian MCP server, which covers both Jira and Confluence. alongside GitHub and Notion. It demonstrates how authentication, access control, and routing work across multiple remote MCP servers through a single gateway.
Note: The demo uses real Jira data via the Atlassian MCP server. A dedicated Confluence demo is coming — the gateway configuration for Confluence works the same way.
Why the Confluence MCP Server Keeps Disconnecting (And How to Fix It)
Session interruptions are the most common complaint from teams trying to use the Confluence MCP server in production. The root cause is Atlassian’s token lifecycle . Here’s what’s happening and what actually fixes it.
What’s driving the disconnections
Atlassian issues OAuth tokens with short expiration windows. MCP clients (e.g., Cursor, Claude) assume tokens will remain valid long enough that aggressive refresh logic isn’t necessary. When Atlassian’s token expires faster than the client anticipates, the session breaks. In interactive clients, that means a re-authentication prompt. In non-interactive tools like automation pipelines, it means silent failure.
The problem can’t be solved by adjusting agent code. It requires an infrastructure-level solution that sits between the client and Atlassian’s endpoint.
What Confluence and Atlassian users are saying
“Are there known issues with connecting MS Copilot and the Atlassian MCP Server? We are seeing authentication issues. We are NOT having issues with the GitHub connectivity.” — Atlassian Community, February 2026
“The auth tokens are very short lived. I have to re-authenticate a lot, at least every day, when I work with it extensively from Cursor. Also integrating the MCP inside flows like n8n is not an option due to the short-lived tokens.” — Atlassian Community member, Dec 2025
How MCP Manager solves it
MCP Manager takes ownership of the Atlassian OAuth session on behalf of your clients. Agents connect to MCP Manager, which manages the underlying connection to Atlassian’s endpoint, monitoring token state and refreshing before expiry, without interrupting whatever the agent is doing. From the client’s perspective, the session never drops. From your team’s perspective, the re-authentication cycle stops entirely.
For automation tools running documentation workflows on a schedule, this is the difference between a reliable integration and one that requires manual intervention every day.
Partial workarounds if you’re not ready for a gateway
- In your Atlassian OAuth configuration, request the offline_access scope — this enables refresh tokens that extend session life beyond the default window.
- For interactive clients like Cursor, a startup script can automate the re-authentication flow so it’s less disruptive.
- For non-interactive automation tools, there is no reliable workaround. A gateway is the only practical solution for unattended Confluence MCP workflows.
FAQs: MCP Gateway for Confluence Integration
What is an MCP gateway and why does Confluence need one?
An MCP gateway is the control and governance layer between your AI agents and your MCP servers. For Confluence, it solves the token timeout problem that interrupts sessions, enforces space-level access controls so agents only reach the content they’re authorized for, logs every interaction for compliance purposes, and filters page content to prevent context window failures during documentation retrieval.
How does a gateway prevent the Confluence MCP server from timing out?
The gateway manages the Atlassian OAuth session centrally. Rather than each client tracking token expiry independently, the gateway refreshes tokens proactively and maintains the connection. Agents and clients connect to the gateway and stay connected — the token lifecycle underneath is handled automatically.
Can I run automated Confluence documentation workflows without a gateway?
Not reliably. Automation tools that run unattended — pipelines that surface documentation on a schedule, agents that update pages based on external triggers — have no mechanism to handle Atlassian’s OAuth re-authentication. A gateway managing the session continuously is the only practical way to run unattended Confluence MCP workflows.
How does MCP Manager handle access control across different Confluence spaces?
MCP Manager’s RBAC lets you define access at the space level, the tool level, or both. You can restrict specific agents to specific spaces — so an agent with access to engineering documentation can’t read HR policy pages, and an agent surfacing customer-facing content can’t write to internal strategy spaces.
What’s the difference between the Confluence MCP server and an MCP gateway?
The Confluence MCP server is Atlassian’s integration that exposes Confluence content to AI agents via the Model Context Protocol. An MCP gateway sits in front of it — governing which agents can access which content, logging what happens, and keeping the connection stable. The server makes Confluence accessible; the gateway makes that access safe and manageable.
Does MCP Manager cover both Confluence and Jira through the same connection?
Yes. MCP Manager connects to the Atlassian remote MCP server, which provides access to both products. You can configure separate access policies for Confluence and Jira — different agents can have different permissions for each product through the same gateway.
Can I connect other tools alongside Confluence through MCP Manager?
Yes. MCP Manager manages multiple MCP servers through a single control plane. The demo above shows the Atlassian MCP server running alongside GitHub and Notion — each with separate access policies, all visible in one dashboard.
Is MCP Manager in the Atlassian Marketplace?
Yes. You can find it in the Atlassian Marketplace alongside Visor, the Jira app built by the same team. For organizations already procuring Atlassian apps through the Marketplace, it’s a straightforward addition.
