docs/servers/providers/proxy.mdx
import { VersionBadge } from '/snippets/version-badge.mdx'
<VersionBadge version="2.0.0" />The Proxy Provider sources components from another MCP server through a client connection. This lets you expose any MCP server's tools, resources, and prompts through your own server, whether the source is local or accessed over the network.
The Proxy Provider enables:
sequenceDiagram
participant Client as Your Client
participant Proxy as FastMCP Proxy
participant Backend as Source Server
Client->>Proxy: MCP Request (stdio)
Proxy->>Backend: MCP Request (HTTP/stdio/SSE)
Backend-->>Proxy: MCP Response
Proxy-->>Client: MCP Response
Create a proxy using create_proxy():
from fastmcp.server import create_proxy
# create_proxy() accepts URLs, file paths, and transports directly
proxy = create_proxy("http://example.com/mcp", name="MyProxy")
if __name__ == "__main__":
proxy.run()
This gives you:
FastMCP proxies are lazy bridges. Creating the proxy object and starting the local server do not contact the upstream server. The upstream connection begins when an MCP client sends an initialize request to the proxy.
During initialization, the proxy initializes the upstream server before responding locally. If the upstream server is unavailable, the URL does not point to an MCP endpoint, or upstream authentication cannot complete, the proxy initialization fails. This keeps the local proxy's connection status aligned with the upstream server it represents.
After initialization, the proxy forwards MCP requests such as ping, tools/list, resources/list, prompts/list, tool calls, resource reads, sampling, elicitation, logging, and progress through the upstream client.
A common use case is bridging transports between servers:
from fastmcp.server import create_proxy
# Bridge HTTP server to local stdio
http_proxy = create_proxy("http://example.com/mcp/sse", name="HTTP-to-stdio")
# Run locally via stdio for Claude Desktop
if __name__ == "__main__":
http_proxy.run() # Defaults to stdio
Or expose a local server via HTTP:
from fastmcp.server import create_proxy
# Bridge local server to HTTP
local_proxy = create_proxy("local_server.py", name="stdio-to-HTTP")
if __name__ == "__main__":
local_proxy.run(transport="http", host="0.0.0.0", port=8080)
create_proxy() provides session isolation - each request gets its own isolated backend session:
from fastmcp.server import create_proxy
# Each request creates a fresh backend session (recommended)
proxy = create_proxy("backend_server.py")
# Multiple clients can use this proxy simultaneously:
# - Client A calls a tool → gets isolated session
# - Client B calls a tool → gets different session
# - No context mixing
If you pass an already-connected client, the proxy reuses that session:
from fastmcp import Client
from fastmcp.server import create_proxy
async with Client("backend_server.py") as connected_client:
# This proxy reuses the connected session
proxy = create_proxy(connected_client)
# ⚠️ Warning: All requests share the same session
Proxies automatically forward MCP protocol features:
| Feature | Description |
|---|---|
| Roots | Filesystem root access requests |
| Sampling | LLM completion requests |
| Elicitation | User input requests |
| Logging | Log messages from backend |
| Progress | Progress notifications |
from fastmcp.server import create_proxy
# All features forwarded automatically
proxy = create_proxy("advanced_backend.py")
# When the backend:
# - Requests LLM sampling → forwarded to your client
# - Logs messages → appear in your client
# - Reports progress → shown in your client
Selectively disable forwarding:
from fastmcp.server.providers.proxy import ProxyClient
backend = ProxyClient(
"backend_server.py",
sampling_handler=None, # Disable LLM sampling
log_handler=None # Disable log forwarding
)
A proxy passes a backend's tool results through untouched, including results that don't match the output schema the backend advertised. Deciding whether a server honored its own contract belongs to the client consuming the result, and that client validates for itself.
This matters when a backend's declared schema is subtly wrong — an enum missing a variant it actually returns, say. A proxy that enforced the schema would replace the backend's working response with an error of its own, and the client would never see what the backend actually said.
from fastmcp import Client
from fastmcp.server import create_proxy
proxy = create_proxy("backend_server.py")
async with Client(proxy) as client:
# The backend's response arrives as the backend sent it. If it violates
# the backend's own output schema, this client raises — its decision.
result = await client.call_tool("get_status")
Skipping the check also avoids a tools/list round trip to the backend on every proxied call, since validation would need the backend's schemas and a proxy builds a fresh connection per request.
A proxy is a server on its front and a client on its back, and the two MCP protocol eras have mutually exclusive interaction models on a single session. On the handshake era (≤2025-11-25) the backend can push server-initiated requests — sampling, elicitation, roots — which the proxy forwards to your client. On the modern era (2026-07-28) those pushes are gone; a backend guard tool instead returns an input request that the proxy relays back as a result. A single proxy session speaks one era, so the whole chain has to agree end-to-end.
By default the proxy relays the era: whatever era your client negotiates on the front, the proxy negotiates the same era on its backend connection, per request. A handshake client reaches a handshake backend, so server-initiated forwarding works; a modern client reaches a modern backend, so a guard tool's input request round-trips. Different clients hitting the same proxy each get a backend session in their own era — the eras never cross.
from fastmcp import Client
from fastmcp.server import create_proxy
# No mode: the backend mirrors each client's negotiated era.
proxy = create_proxy("backend_server.py")
# A handshake client gets a handshake backend (push-forwarding works).
async with Client(proxy, mode="legacy") as client:
...
# A modern client gets a modern backend (guard tools round-trip).
async with Client(proxy, mode="auto") as client:
...
Passing an explicit mode pins the backend to one era regardless of the client:
# Always negotiate the modern era upstream, whatever the client speaks.
proxy = create_proxy("backend_server.py", mode="auto")
Pinning breaks the end-to-end era agreement, so reserve it for a backend that only speaks one era. When the client's era and the pinned backend era disagree on a feature — a modern client asking for a guard round-trip against a handshake-pinned backend, say — the mismatch surfaces through the normal era gates rather than silently degrading. Mirroring applies to proxies created from a target the proxy connects itself (a URL, path, config, or FastMCP instance); when you hand create_proxy an already-configured Client, that client carries its own mode and mirroring does not override it.
A multi-server configuration adds a hop: FastMCP mounts one proxy per configured server onto a router, and your client talks to that router rather than to any backend directly. The era carries through the whole depth, so each real backend negotiates the era your client did — not just the router in front of them.
proxy = create_proxy(
{
"mcpServers": {
"weather": {"url": "https://weather.example.com/mcp"},
"calendar": {"url": "https://calendar.example.com/mcp"},
}
}
)
A modern client here reaches both weather and calendar on modern sessions, so a guard tool on either one round-trips end to end. An explicit mode pins every backend in the configuration, the same way it pins a single one.
Create proxies from configuration dictionaries:
from fastmcp.server import create_proxy
config = {
"mcpServers": {
"default": {
"url": "https://example.com/mcp",
"transport": "http"
}
}
}
proxy = create_proxy(config, name="Config-Based Proxy")
Combine multiple servers with automatic namespacing:
from fastmcp.server import create_proxy
config = {
"mcpServers": {
"weather": {
"url": "https://weather-api.example.com/mcp",
"transport": "http"
},
"calendar": {
"url": "https://calendar-api.example.com/mcp",
"transport": "http"
}
}
}
# Creates unified proxy with prefixed components:
# - weather_get_forecast
# - calendar_add_event
composite = create_proxy(config, name="Composite")
Proxied components follow standard prefixing rules:
| Component Type | Pattern |
|---|---|
| Tools | {prefix}_{tool_name} |
| Prompts | {prefix}_{prompt_name} |
| Resources | protocol://{prefix}/path |
| Templates | protocol://{prefix}/... |
Components from a proxy server are "mirrored" - they reflect the remote server's state and cannot be modified directly.
To modify a proxied component (like disabling it), create a local copy:
from fastmcp import FastMCP
from fastmcp.server import create_proxy
proxy = create_proxy("backend_server.py")
# Get mirrored tool
mirrored_tool = await proxy.get_tool("useful_tool")
# Create modifiable local copy
local_tool = mirrored_tool.copy()
# Add to your own server
my_server = FastMCP("MyServer")
my_server.add_tool(local_tool)
# Now you can control enabled state
my_server.disable(keys={local_tool.key})
Proxying introduces network latency:
| Operation | Local | Proxied (HTTP) |
|---|---|---|
list_tools() | 1-2ms | 300-400ms |
call_tool() | 1-2ms | 200-500ms |
When mounting proxy servers, this latency affects all operations on the parent server.
ProxyProvider caches the backend's component lists (tools, resources, templates, prompts) so that individual lookups — like resolving a tool by name during call_tool — don't require a separate backend connection. The cache stores raw component metadata and is shared across all proxy sessions; per-session visibility, auth, and transforms are still applied after cache lookup by the server layer. The cache refreshes whenever an explicit list_* call is made, and entries expire after a configurable TTL (default 300 seconds).
For backends whose component lists change dynamically, disable caching by setting cache_ttl=0.
from fastmcp.server.providers.proxy import ProxyProvider, ProxyClient
# Default 300s TTL
provider = ProxyProvider(lambda: ProxyClient("http://backend/mcp"))
# Custom TTL
provider = ProxyProvider(lambda: ProxyClient("http://backend/mcp"), cache_ttl=60)
# Disable caching
provider = ProxyProvider(lambda: ProxyClient("http://backend/mcp"), cache_ttl=0)
By default, each tool call opens a fresh MCP session to the backend. This is the safe default because it prevents state from leaking between requests. However, for stateless HTTP backends where there's no session state to protect, this overhead is unnecessary.
You can reuse a single backend session by providing a client factory that returns the same client instance:
from fastmcp.server.providers.proxy import FastMCPProxy, ProxyClient
base_client = ProxyClient("http://backend:8000/mcp")
shared_client = base_client.new()
proxy = FastMCPProxy(
client_factory=lambda: shared_client,
name="ReusedSessionProxy",
)
This eliminates the MCP initialization handshake on every call, which can dramatically reduce latency under load. The Client uses reference counting for its session lifecycle, so concurrent callers sharing the same instance is safe.
For explicit session control, use FastMCPProxy directly:
from fastmcp.server.providers.proxy import FastMCPProxy, ProxyClient
# Custom session factory
def create_client():
return ProxyClient("backend_server.py")
proxy = FastMCPProxy(client_factory=create_client)
This gives you full control over session creation and reuse strategies.
Mount a proxy to add components from another server:
from fastmcp import FastMCP
from fastmcp.server import create_proxy
server = FastMCP("My Server")
# Add local tools
@server.tool
def local_tool() -> str:
return "Local result"
# Mount proxied tools from another server
external = create_proxy("http://external-server/mcp")
server.mount(external)
# Now server has both local and proxied tools