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Bifrost MCP Gateway

Open-source AI gateway that can connect to downstream MCP servers and expose their aggregated tools through a single HTTP or SSE MCP endpoint for Claude Desktop, Cursor, and other MCP clients.

by maximhq · submitted by oktofeesh1·added 2026-06-06·
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Source URLs
https://github.com/maximhq/bifrost/blob/main/docs/mcp/overview.mdx, https://github.com/maximhq/bifrost
Brand
Bifrost
Brand domain
getbifrost.ai
Brand asset source
brandfetch
Safety notes
Bifrost can expose all selected downstream MCP tools through one `/mcp` gateway endpoint, so treat the endpoint like an access layer for every connected tool., The docs state that default LLM tool calls are suggestions until an explicit tool execution API call is made, but agent mode can enable configured automatic execution., Gateway-mode auto-approval is controlled by the external MCP host, such as Claude Desktop, Cursor, Cline, or a custom client, not by Bifrost's `tools_to_auto_execute` setting., Stdio connections spawn local commands inside the Bifrost runtime; Docker deployments need images that include the requested executables., Use virtual keys, per-tool allowlists, auth headers, OAuth, per-user credentials, and network controls to limit which clients can reach high-impact tools.
Privacy notes
Bifrost may process provider prompts, model responses, MCP tool names, tool arguments, tool results, headers, virtual keys, OAuth tokens, per-user credentials, logs, traces, metrics, and downstream server metadata., Per-user auth stores credentials against a signed-in user, virtual key, or session identity; review credential lifecycle, revocation, and orphaned-session behavior., Logs, config stores, provider settings, MCP sessions, and gateway analytics can contain sensitive operational or user data., Keep real provider keys, virtual keys, OAuth secrets, MCP endpoint URLs, and upstream service credentials in environment variables or secret stores, not committed config.
Author
maximhq
Submitted by
oktofeesh1
Claim status
unclaimed
Last verified
2026-06-06

Decision playbook

Review trust signals before you adopt

Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.

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Selected

0

Current score

63

Baseline

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No baseline selected

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Source and provenance checks

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  • Metadata reviewed

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Safety and privacy checks

Complete

Validate risk disclosures before installation or API wiring.

  • Safety notes presentRequired

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    Done
  • Privacy notes presentRequired

    Review data handling notes before connecting accounts or secrets.

    Done
  • Trust level risk gateRequired

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Package and install checks

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Setup at a glance

CLI install

Copy-ready — paste the snippet to get started.

25 minutes

Adoption plan

Balanced adoption plan

Current risk score 24/100. Use staged verification before broader rollout.

Risk 24

Pre-adoption checks

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Security checks

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Rollout

Adopt in controlled steps based on the selected plan.

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    Roll out to a small cohort before wider usage.

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    Define rollback path and monitor errors after adoption.

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Evidence readiness

Evidence readiness matrix · balanced

Missing required evidence: Metadata review. Risk score 31.

Risk 31

Source provenance

Present

Source repository/provenance is listed.

Required in this preset

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Missing

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Safety notes

Present

Safety notes are present.

Required in this preset

Privacy notes

Present

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Optional in this preset

Package integrity

Missing

Package integrity metadata is missing.

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Install payload

Present

Install payload is available.

Required in this preset

Required gaps: Metadata review

Decision timeline

Decision timeline · balanced

Blocking gaps: Check metadata review status. Risk 28.

Risk 28

triage

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triage

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verify

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Done

verify

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rollout

Verify install payload and commandsRequired

Install payload is available.

Done

Blockers: Check metadata review status

Prerequisite readiness

Prerequisite readiness

5 prerequisites to line up before setup. Have accounts and credentials ready first.

0/5 ready
Account & credentials2Network & hosting2General125 minutes

Safety & privacy surface

Safety & privacy surface

5 safety and 4 privacy notes across 3 risk areas. Review closely: credentials & tokens, network access.

3 areas
  • SafetyNetwork accessBifrost can expose all selected downstream MCP tools through one `/mcp` gateway endpoint, so treat the endpoint like an access layer for every connected tool.
  • SafetyNetwork accessThe docs state that default LLM tool calls are suggestions until an explicit tool execution API call is made, but agent mode can enable configured automatic execution.
  • SafetyExecution & processesGateway-mode auto-approval is controlled by the external MCP host, such as Claude Desktop, Cursor, Cline, or a custom client, not by Bifrost's `tools_to_auto_execute` setting.
  • SafetyNetwork accessStdio connections spawn local commands inside the Bifrost runtime; Docker deployments need images that include the requested executables.
  • SafetyCredentials & tokensUse virtual keys, per-tool allowlists, auth headers, OAuth, per-user credentials, and network controls to limit which clients can reach high-impact tools.
  • PrivacyCredentials & tokensBifrost may process provider prompts, model responses, MCP tool names, tool arguments, tool results, headers, virtual keys, OAuth tokens, per-user credentials, logs, traces, metrics, and downstream server metadata.
  • PrivacyCredentials & tokensPer-user auth stores credentials against a signed-in user, virtual key, or session identity; review credential lifecycle, revocation, and orphaned-session behavior.
  • PrivacyCredentials & tokensLogs, config stores, provider settings, MCP sessions, and gateway analytics can contain sensitive operational or user data.
  • PrivacyCredentials & tokensKeep real provider keys, virtual keys, OAuth secrets, MCP endpoint URLs, and upstream service credentials in environment variables or secret stores, not committed config.

Safety notes

  • Bifrost can expose all selected downstream MCP tools through one `/mcp` gateway endpoint, so treat the endpoint like an access layer for every connected tool.
  • The docs state that default LLM tool calls are suggestions until an explicit tool execution API call is made, but agent mode can enable configured automatic execution.
  • Gateway-mode auto-approval is controlled by the external MCP host, such as Claude Desktop, Cursor, Cline, or a custom client, not by Bifrost's `tools_to_auto_execute` setting.
  • Stdio connections spawn local commands inside the Bifrost runtime; Docker deployments need images that include the requested executables.
  • Use virtual keys, per-tool allowlists, auth headers, OAuth, per-user credentials, and network controls to limit which clients can reach high-impact tools.

Privacy notes

  • Bifrost may process provider prompts, model responses, MCP tool names, tool arguments, tool results, headers, virtual keys, OAuth tokens, per-user credentials, logs, traces, metrics, and downstream server metadata.
  • Per-user auth stores credentials against a signed-in user, virtual key, or session identity; review credential lifecycle, revocation, and orphaned-session behavior.
  • Logs, config stores, provider settings, MCP sessions, and gateway analytics can contain sensitive operational or user data.
  • Keep real provider keys, virtual keys, OAuth secrets, MCP endpoint URLs, and upstream service credentials in environment variables or secret stores, not committed config.

Prerequisites

  • Node.js with `npx`, Docker, or another supported Bifrost Gateway deployment path.
  • Bifrost Gateway version `v1.4.0-prerelease1` or newer for MCP gateway mode.
  • Downstream MCP server commands or HTTP/SSE endpoint URLs prepared before registering clients.
  • Provider API keys, virtual keys, gateway auth settings, and governance policies reviewed before sharing the endpoint.
  • Network, TLS, storage, log retention, and secret management decisions made before exposing Bifrost outside a trusted environment.

Schema details

Install type
cli
Troubleshooting
No
Source repository stats
Scope
Source repo
Collection metadata
Estimated setup
25 minutes
Difficulty
advanced
Full copyable content
{
  "mcpServers": {
    "bifrost": {
      "url": "BIFROST_MCP_URL",
      "headers": {
        "Authorization": "Bearer ${BIFROST_VIRTUAL_KEY}"
      }
    }
  }
}

About this resource

Content

Bifrost is an Apache-licensed AI gateway from Maxim that includes MCP client and MCP server capabilities. In gateway deployments, it can connect to downstream MCP servers over stdio, HTTP, or SSE, discover their tools, and expose the selected tools through a single /mcp endpoint for Claude Desktop, Cursor, Cline, and other MCP-compatible clients.

The MCP docs distinguish two common modes. Bifrost can act as an MCP client for external servers, and it can also act as an MCP server that publishes an aggregated tool registry to external MCP hosts. The gateway endpoint supports JSON-RPC POST requests and SSE connections, with optional virtual-key authentication and per-key tool filtering.

Source Review

These sources were reviewed on 2026-06-06. Prefer the live repository, MCP overview, MCP gateway docs, connection docs, auth docs, Docker image page, and license file for current version requirements, deployment options, auth behavior, and MCP endpoint details.

Features

  • Connect Bifrost to downstream MCP servers over stdio, HTTP, or SSE.
  • Expose aggregated MCP tools through Bifrost's /mcp gateway endpoint.
  • Support JSON-RPC POST and SSE gateway connections for compatible MCP clients.
  • Configure virtual-key-specific MCP servers and per-key tool allowlists.
  • Use server-level headers, OAuth, per-user OAuth, or per-user header auth for HTTP and SSE upstreams.
  • Manage downstream MCP clients through the web UI, API, or config.json.
  • Inspect connected MCP tools and enable or disable selected tools.
  • Store per-user MCP credentials against user, virtual-key, or session identities.
  • Combine MCP routing with Bifrost's provider gateway, logging, metrics, governance, and config stores.
  • Register in-process custom tools when embedding Bifrost as a Go SDK application.

Installation

The README documents npx and Docker gateway startup paths. The shortest local start is:

npx -y @maximhq/bifrost

After the gateway starts, register downstream MCP clients through the MCP Gateway UI, the management API, or the mcp.client_configs section in config.json. Use environment references for sensitive connection strings and secrets.

For external MCP clients, configure the client to connect to the Bifrost MCP gateway endpoint and include any required virtual-key auth header:

{
  "mcpServers": {
    "bifrost": {
      "url": "BIFROST_MCP_URL",
      "headers": {
        "Authorization": "Bearer ${BIFROST_VIRTUAL_KEY}"
      }
    }
  }
}

The upstream docs note that Bifrost's MCP gateway feature requires the Gateway deployment and v1.4.0-prerelease1 or newer.

Use Cases

  • Give Claude one governed endpoint for a curated group of internal MCP tools.
  • Publish separate MCP tool sets for production, development, admin, or analyst virtual keys.
  • Connect local stdio tools, remote HTTP tools, and SSE tools behind one gateway.
  • Require per-user OAuth or header credentials before a downstream tool executes.
  • Use Bifrost's provider gateway and MCP gateway together in agent workflows.
  • Audit MCP traffic through gateway logs, metrics, sessions, and config stores.
  • Filter risky file, database, browser, shell, or production tools before exposing them to a client.
  • Host custom in-process tools in a Go application that embeds Bifrost.

Safety and Privacy

Bifrost is gateway infrastructure. A single MCP endpoint can expose many downstream tools, so configure virtual keys, tool allowlists, auth modes, network access, TLS, and host-side approval rules before sharing it with agent clients. Be especially careful with downstream servers that can read or write files, run shell commands, change infrastructure, query production databases, or modify third-party accounts.

The docs emphasize that default LLM tool calls are not executed automatically without an explicit tool execution call, but agent mode can be configured for automatic execution. In pure MCP gateway mode, the external host decides whether tool calls need user approval. Review the approval settings in Claude Desktop, Cursor, Cline, or any custom MCP client that connects to Bifrost.

Bifrost can handle provider credentials, virtual keys, MCP auth headers, OAuth tokens, per-user credentials, prompts, model responses, tool arguments, tool results, request logs, traces, metrics, and config-store data. Treat those stores as sensitive, keep secrets out of committed config, and define log retention before routing production traffic through the gateway.

Duplicate Check

No maximhq/bifrost entry, Bifrost MCP Gateway entry, or matching source URL was found in content/mcp or the broader content directories.

Source citations

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How it compares

Bifrost MCP Gateway side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

Field

Open-source AI gateway that can connect to downstream MCP servers and expose their aggregated tools through a single HTTP or SSE MCP endpoint for Claude Desktop, Cursor, and other MCP clients.

Open dossier

Docker's MCP CLI plugin and gateway for running catalog, OCI, registry, or local-file MCP servers in containers and exposing them to Claude, Cursor, VS Code, and other MCP clients through a shared gateway profile.

Open dossier

Dashboard, CLI, and gateway for centrally managing many MCP servers and exposing them as authenticated all-server, group, single-server, or smart routing endpoints.

Open dossier

AGPL-licensed MCP-native platform with a private MCP registry, MCP gateway, Kubernetes MCP orchestrator, access control, credential resolution, observability, and deterministic tool guardrails for shared AI deployments.

Open dossier
Next steps
Trust
Review statusNot reviewedNot reviewedNot reviewedNot reviewed
Package trustPackage not verifiedPackage not verifiedPackage not verifiedPackage not verified
Source provenanceSource-backedSource-backedSource-backedSource-backed
Submitteroktofeesh1oktofeesh1oktofeesh1oktofeesh1
Install riskReview firstReview firstReview firstReview first
Notes Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓
BrandBifrost logoBifrostDocker MCP Gateway logoDocker MCP GatewayMCPHub logoMCPHubArchestra logoArchestra
Categorymcpmcpmcpmcp
SourceSource-backedSource-backedSource-backedSource-backed
Authormaximhqdockersamanhappyarchestra-ai
Added2026-06-062026-06-062026-06-052026-06-06
Platforms
Harness
Source repo
Safety notesBifrost can expose all selected downstream MCP tools through one `/mcp` gateway endpoint, so treat the endpoint like an access layer for every connected tool. The docs state that default LLM tool calls are suggestions until an explicit tool execution API call is made, but agent mode can enable configured automatic execution. Gateway-mode auto-approval is controlled by the external MCP host, such as Claude Desktop, Cursor, Cline, or a custom client, not by Bifrost's `tools_to_auto_execute` setting. Stdio connections spawn local commands inside the Bifrost runtime; Docker deployments need images that include the requested executables. Use virtual keys, per-tool allowlists, auth headers, OAuth, per-user credentials, and network controls to limit which clients can reach high-impact tools.Docker MCP Gateway can start and route multiple MCP servers, so each connected client inherits the permissions of every enabled server and tool. Container isolation reduces host exposure, but Docker Engine or Docker socket access is still highly privileged and should be limited to trusted users. The gateway supports tool allowlists, CPU limits, memory limits, network blocking, secret blocking, image signature verification, and interceptors; review defaults before production use. Catalog, profile, local-file, and registry references can change which servers run behind the gateway, especially when watch mode or shared profiles are enabled. Tool-call logging is enabled by default in the documented flags, so avoid routing secrets or sensitive payloads unless logging and retention are controlled.MCPHub centralizes many downstream MCP servers, so one hub endpoint can expose broad read, write, file, shell, browser, database, or account capabilities depending on the registered servers. The Docker command binds the dashboard and gateway to 127.0.0.1 by default; use a reverse proxy with TLS and explicit access controls before exposing MCPHub on a network interface. MCP endpoints require authentication by default; do not disable bearer authentication outside trusted local testing. Smart routing can discover and invoke tools by semantic similarity, so keep group visibility and bearer-key scopes narrow. Hot-swappable configuration can add, remove, or change downstream MCP server access while the hub is running. OAuth server mode, OAuth client mode, social login, and database mode introduce additional credential and session management responsibilities.Archestra is a platform/control-plane entry, not a single-purpose local MCP helper; admins can expose many MCP servers, agents, tools, and credentials through one gateway. The upstream quickstart mounts the host Docker socket so the platform can run MCP servers; treat that as highly privileged host access and avoid using it on sensitive machines without isolation. Self-hosted MCP servers may run as Kubernetes workloads with injected environment variables, secrets, images, network policies, and restart controls. Tool assignments, gateway visibility, credential resolution, custom headers, and load-tools-on-demand settings should be reviewed per team and environment. Deterministic tool guardrails can reduce some unsafe tool chains, but they depend on correct policies and do not make untrusted MCP servers safe by default.
Privacy notesBifrost may process provider prompts, model responses, MCP tool names, tool arguments, tool results, headers, virtual keys, OAuth tokens, per-user credentials, logs, traces, metrics, and downstream server metadata. Per-user auth stores credentials against a signed-in user, virtual key, or session identity; review credential lifecycle, revocation, and orphaned-session behavior. Logs, config stores, provider settings, MCP sessions, and gateway analytics can contain sensitive operational or user data. Keep real provider keys, virtual keys, OAuth secrets, MCP endpoint URLs, and upstream service credentials in environment variables or secret stores, not committed config.Docker MCP Gateway may process MCP server definitions, catalog entries, profile exports, local server files, secrets, OAuth tokens, tool names, tool arguments, tool outputs, logs, container metadata, and Docker Engine metadata. Secrets may come from Docker Desktop secrets or `.env` fallback files; keep those stores out of version control and restrict filesystem permissions. Tool outputs can include local files, API responses, credentials, account data, or infrastructure details depending on the enabled downstream MCP servers. Exported profiles and catalogs can reveal internal server names, image references, allowed tools, configuration values, and service endpoints.MCPHub may handle prompts, tool names, tool arguments, tool results, server configs, resource data, bearer keys, OAuth tokens, login sessions, user identities, logs, and CLI command history. Mounted config files, data directories, database rows, vector indexes, generated passwords, and dashboard screenshots can reveal sensitive server names, environment variables, credentials, and tool schemas. Downstream MCP servers may forward private workspace, browser, database, cloud, ticketing, or account data through MCPHub to connected clients and model providers. Do not commit real `mcp_settings.json` files, bearer keys, OAuth secrets, social-login credentials, database URLs, generated admin passwords, or exported hub data.MCP server definitions, tool schemas, gateway tokens, upstream credentials, OAuth tokens, API keys, custom headers, logs, traces, and tool results may be stored or processed by the platform. Built-in observability, LLM proxy, chat, agents, and policy features can reveal prompts, tool arguments, tool outputs, token usage, user identities, team membership, and trace metadata. Registry entries and installations can use personal, team-scoped, or shared credentials; choose the narrowest scope that matches the use case. When external MCP clients call an Archestra gateway, downstream tool results can still be sent by the MCP client to the configured model provider.
Prerequisites
  • Node.js with `npx`, Docker, or another supported Bifrost Gateway deployment path.
  • Bifrost Gateway version `v1.4.0-prerelease1` or newer for MCP gateway mode.
  • Downstream MCP server commands or HTTP/SSE endpoint URLs prepared before registering clients.
  • Provider API keys, virtual keys, gateway auth settings, and governance policies reviewed before sharing the endpoint.
  • Docker Desktop `4.59+` with the MCP Toolkit feature enabled, or the Docker MCP CLI plugin built and installed independently.
  • Docker Engine access for running containerized MCP servers and the gateway.
  • MCP server sources prepared from Docker MCP Catalog entries, OCI images, MCP Registry entries, or local YAML/JSON server files.
  • Profiles feature enabled when using `docker mcp profile` and profile-based gateway runs outside Docker Desktop.
  • Docker available for the documented container deployment.
  • A reviewed `mcp_settings.json` file for the MCP servers the hub should launch or proxy.
  • A durable mounted data directory so credentials, generated passwords, sessions, and state survive restarts.
  • OpenSSL or another secure random generator available to create a unique administrator password.
  • Docker for local evaluation, or Kubernetes and Helm/Terraform-style deployment planning for production use.
  • Organization policy for which MCP servers, credentials, teams, environments, and external network destinations may be exposed.
  • LLM provider keys or local model configuration if using Archestra's built-in chat, agents, or LLM proxy features.
  • Admin review of the quickstart container command before mounting the Docker socket.
Install
npx -y @maximhq/bifrost
docker mcp gateway run
docker run -p 127.0.0.1:3000:3000 -v ./mcp_settings.json:/app/mcp_settings.json -v ./data:/app/data -e ADMIN_PASSWORD="$(openssl rand -hex 24)" samanhappy/mcphub
docker pull archestra/platform:latest
Config
{
  "mcpServers": {
    "bifrost": {
      "url": "BIFROST_MCP_URL",
      "headers": {
        "Authorization": "Bearer ${BIFROST_VIRTUAL_KEY}"
      },
      "type": "http"
    }
  }
}
{
  "mcpServers": {
    "MCP_DOCKER": {
      "command": "docker",
      "args": [
        "mcp",
        "gateway",
        "run"
      ]
    }
  }
}
Manual-only setup:
{
  "mcpServers": {
    "time": {
      "command": "npx",
      "args": ["-y", "time-mcp"]
    },
    "fetch": {
      "command": "uvx",
      "args": ["mcp-server-fetch"]
    }
  }
}
{
  "mcpServers": {
    "archestra": {
      "url": "LOCAL_ARCHESTRA_MCP_GATEWAY_URL",
      "headers": {
        "Authorization": "Bearer ARCHESTRA_GATEWAY_TOKEN"
      }
    }
  }
}
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