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Keep your ASP.NET Core REST API as the source of business rules, then add a narrowly scoped MCP server endpoint beside it. The official ModelContextProtocol.AspNetCore package exposes selected operations as discoverable tools. Publish that endpoint over Streamable HTTP, protect it with the same authentication and tenant checks as your REST routes, and register its HTTPS URL with the AI client. Claude supports MCP connectors across Claude.ai, Claude Desktop, Claude Code and the Messages API. Google’s documented remote-MCP path for the Gemini Interactions API requires Streamable HTTP and does not support SSE.
What MCP adds to an existing .NET API
Model Context Protocol (MCP) is an open standard for connecting AI applications to tools and data. It does not replace your REST API, domain model, database, or authorization system. Instead, it adds a machine-readable tool surface that an AI host can discover and call.
A useful architecture is:
- REST controllers: remain the public application API for web, mobile and integration clients.
- Application services: continue to hold validation, business rules, transactions and tenant isolation.
- MCP tools: translate an AI-friendly request into a call to those same application services.
- Authentication and authorization: run at the MCP boundary and inside the service layer, just as they do for REST.
This arrangement avoids maintaining two implementations of an operation. An MCP tool should be a task-oriented capability such as find_open_orders or create_support_ticket, not a thin mirror of every controller action. Do not expose administrative, destructive or high-volume operations merely because they already exist as REST endpoints.
Prerequisites and version decisions
- An ASP.NET Core application targeting a supported .NET runtime. The NuGet listing captured for this guide shows compatibility entries for .NET 8, .NET 9 and .NET 10.
- A package version pinned in your project file. The captured NuGet result lists
ModelContextProtocol2.2.0; package and protocol revisions move quickly, so verify the version and release notes when you implement. - An HTTPS address reachable by the remote client. Localhost-only endpoints work for local development but are not remote MCP servers.
- An authentication scheme that can identify the caller and, where applicable, its tenant.
Microsoft’s .NET guidance describes the C# SDK as an official implementation maintained with the MCP community. A Microsoft .NET Blog update dated March 5, 2026 reports that the SDK reached its v1.0 milestone with support for the 2025-11-25 MCP specification. Treat both the package API and protocol revision as versioned dependencies rather than permanent constants.
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Install the official server packages
The HTTP server package is ModelContextProtocol.AspNetCore. Microsoft’s getting-started material also shows this prerelease installation command:
dotnet add package ModelContextProtocol --prereleaseFor a production application, add the HTTP package explicitly and pin a version that you have checked against your target runtime and protocol revision:
dotnet add package ModelContextProtocol.AspNetCore --version 2.2.0The version above reflects the NuGet result available for this guide; use the release you have actually validated rather than copying it blindly. If the SDK has moved to a newer major or prerelease API, update the registration and tool attributes together.
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Register MCP beside your REST routes
An HTTP MCP server is a normal ASP.NET Core application. That means your existing dependency injection, configuration, logging, health checks, authentication middleware and deployment pipeline still apply. A representative registration looks like this; method names can change between SDK releases, so check the package documentation for the pinned version:
var builder = WebApplication.CreateBuilder(args);
builder.Services.AddAuthentication()
.AddJwtBearer();
builder.Services.AddAuthorization();
builder.Services.AddScoped<OrderService>();
builder.Services
.AddMcpServer()
.WithHttpTransport()
.WithToolsFromAssembly();
var app = builder.Build();
app.UseAuthentication();
app.UseAuthorization();
app.MapControllers();
app.MapMcp("/mcp");
app.Run();The important properties are conceptual: register the MCP server in dependency injection, select HTTP transport, discover only the tool classes you intend to publish, and map a stable endpoint such as /mcp. Keep the endpoint separate from ordinary controller routes so that monitoring, rate limits and authorization rules can distinguish tool traffic.
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Expose narrowly scoped tools
Wrap an application service, not a controller
Controllers often return HTTP-specific types, status codes and headers. MCP tools should call an application service that accepts a validated command and returns a predictable result. This keeps REST and MCP behavior consistent.
public sealed record FindOpenOrdersRequest(
string CustomerId,
int Limit = 20);
public sealed record OpenOrderSummary(
string OrderId,
string Status,
decimal Total);
[McpServerToolType]
public sealed class OrderTools
{
private readonly OrderService _orders;
public OrderTools(OrderService orders) => _orders = orders;
[McpServerTool, Description("List open orders for the authenticated customer.")]
public async Task<IReadOnlyList<OpenOrderSummary>> FindOpenOrders(
FindOpenOrdersRequest request,
CancellationToken cancellationToken)
{
if (string.IsNullOrWhiteSpace(request.CustomerId))
throw new ArgumentException("CustomerId is required.");
if (request.Limit is < 1 or > 100)
throw new ArgumentOutOfRangeException(nameof(request.Limit));
return await _orders.FindOpenOrdersAsync(
request.CustomerId,
request.Limit,
cancellationToken);
}
}Attribute names and overloads depend on the SDK version. The design rules do not: give every tool a concrete verb-plus-object name, describe what it does in one sentence, mark required and optional inputs, enforce bounds in code, and return a stable shape. If a client supports structured content, return structured fields rather than a paragraph that the model must parse.
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Read tools are easier to retry and audit. A write tool should state whether it is idempotent, require an explicit confirmation field when appropriate, and return the created resource identifier. Never rely on the model to decide whether a caller is allowed to perform an operation. Authorization must use the authenticated principal and server-side policy.
Preserve tenant boundaries
Do not accept a tenant ID as an untrusted free-form argument and then use it as the security boundary. Derive tenant context from claims, mTLS identity or another verified credential, and pass that context into the same service methods used by REST. If a customer ID is an argument, verify that it belongs to the caller’s tenant before querying.
Choose the transport: stdio or Streamable HTTP
| Transport | Best fit | Deployment shape | Important constraint |
|---|---|---|---|
| stdio | A local desktop or command-line host launching the server as a child process | The client starts the .NET process and exchanges messages through standard input and output | Not a remotely addressable HTTPS service; process lifetime and local permissions are part of the integration |
| Streamable HTTP | Remote Claude or Gemini clients and hosted infrastructure | A stable HTTPS endpoint behind your normal ASP.NET Core hosting, proxy and observability stack | Requires network reachability, authentication and careful timeout and concurrency settings |
For a server that remote clients will call, use Streamable HTTP. Google’s current remote-MCP documentation for the Interactions API explicitly supports Streamable HTTP and says SSE servers are not supported on that path. Do not select SSE because an older example uses it; verify the transport supported by the exact client and SDK version you are deploying.
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Connect Claude
Anthropic documents MCP connectors for Claude.ai, Claude Desktop, Claude Code and the Messages API. The connection details differ by product, including authentication and plan requirements, so configure the MCP server in the product’s current connector or tool settings rather than assuming one universal screen.
Regardless of the Claude surface, provide:
- The public HTTPS MCP endpoint, for example
https://api.example.com/mcp. - The authentication method and required headers or OAuth flow.
- A small allow-list of tools suitable for the intended workflow.
- A redirect, firewall and certificate configuration that permits the selected Claude service to reach the endpoint.
After registration, verify that Claude can first discover the tool schema, then call a harmless read operation. Test a denied operation separately; a successful discovery does not prove that authorization is correct.
Connect Gemini
Remote MCP through the Interactions API
Google’s documented remote-MCP configuration supplies a server name and url, with optional headers and an allowed_tools list. A conceptual request configuration is:
{
"type": "mcp_server",
"name": "orders-api",
"url": "https://api.example.com/mcp",
"allowed_tools": ["find_open_orders"],
"headers": {
"Authorization": "Bearer <token>"
}
}Use the field names and authentication mechanism from the current Gemini API schema; the example illustrates the shape, not a credential to copy. The remote server must use Streamable HTTP. SSE is not supported for this documented remote path.
SDK-managed tool execution
Google’s legacy Generate Content function-calling documentation describes Gemini SDKs that can automatically execute MCP tools and continue the request/response loop until no more tool calls are made. Treat that as SDK behavior, not a guarantee for every model, library or future release. Pin the Gemini SDK, inspect its MCP support, and set execution limits so a prompt cannot trigger an unbounded sequence of calls.
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Authentication, authorization and safety controls
Put the same authentication middleware in front of /mcp that protects sensitive REST routes, then apply policy checks inside each tool and service. A model-generated tool name or argument is never an authorization decision.
- Use least privilege: publish only the tools required for a workflow. Host-side allow-lists, such as Gemini’s documented
allowed_toolsoption, provide an additional boundary. - Validate every argument: enforce length, enum, range, format and maximum-page-size rules before calling the service.
- Protect writes: require idempotency keys where retries could duplicate an action, and log the authenticated subject for every mutation.
- Limit data returned: redact secrets and unnecessary personal data before serializing a result.
- Apply operational limits: configure request timeouts, concurrency limits, payload limits and rate limits appropriate to your infrastructure.
- Audit tool calls: record tool name, caller, tenant, validation outcome, latency and downstream result without storing sensitive prompt content unnecessarily.
Stateless versus stateful HTTP
| Mode | Use when | Scaling and operations |
|---|---|---|
| Stateless | Each request contains enough identity and arguments to reconstruct context, and long-lived server sessions are unnecessary | Simpler horizontal scaling, easier failover and fewer session-storage concerns |
| Stateful | A workflow needs server-side continuity, negotiated session data or expensive context that should persist between calls | Requires session lifetime rules, shared state or affinity, and explicit cleanup and recovery behavior |
The official C# SDK conceptual material covers both modes. For most CRUD-style REST integrations, start stateless and add state only when a demonstrated workflow requires it.
Deployment options
| Option | Strengths | Questions to answer |
|---|---|---|
| Existing ASP.NET Core host | Reuses your current deployment, authentication, logging, health checks and network controls | Can the host expose a stable HTTPS route, enforce MCP-specific limits and isolate tool traffic in observability? |
| Containerized ASP.NET Core service | Separates MCP scaling and release cadence from the main API while retaining the same .NET runtime model | How will you provide secrets, certificates, ingress, autoscaling and distributed tracing? |
| Azure Functions remote MCP server | Useful when your organization already operates serverless workloads and event-driven integrations | Check current hosting limits, authentication flow, cold-start behavior and pricing before choosing it. |
Docker deployment for an ASP.NET Core MCP server using Streamable HTTP is covered by the official C# SDK guidance. Azure documentation also describes remote MCP servers with Azure Functions and an Azure MCP Server. Hosting limits, authentication details and prices change, so validate them against the service documentation for your region and plan.
Testing before you give an AI access
No independent benchmark or compatibility test establishes a universal latency or success rate for this integration. Treat testing as an engineering requirement for your application:
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- Happy path: call a read tool with valid arguments and verify the result shape and tenant scope.
- Schema failures: omit required fields, use wrong types and exceed limits; confirm a clear validation error without a downstream call.
- Authorization failures: use a token from another tenant and a principal lacking the required policy; expect denial and an audit event.
- Mutation safety: retry a write request and verify idempotency or an explicit duplicate response.
- Timeouts and cancellation: interrupt a slow downstream operation and ensure cancellation reaches the service without leaving partial state.
- Load and outage behavior: test rate limits, dependency failures, proxy buffering and reconnects using the same Streamable HTTP path used in production.
Troubleshoot the common failures
The client cannot discover any tools
- Confirm the URL is the MCP route, not a controller route or health endpoint.
- Check that the reverse proxy forwards the required HTTP methods, streaming responses and authentication headers.
- Verify that tool classes are registered or discoverable in the assembly loaded by the application.
- Inspect server logs for protocol-version or package-version mismatches.
Gemini reports an unsupported transport
For remote Gemini MCP, replace SSE with Streamable HTTP and ensure the URL points to that endpoint. The documented remote path does not support SSE.
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A tool returns data from the wrong tenant
Stop exposing tenant selection as a trusted argument. Derive tenant context from the authenticated identity, enforce it again in the application service and add a regression test using two tenants.
Calls repeat or create duplicates
Assume that clients may retry after a timeout. Add an idempotency key to mutating commands, persist the result associated with that key and return the original result for a safe retry.
The server works locally but not remotely
Check public DNS, certificate validity, ingress rules, firewall egress from the AI host, proxy timeouts and whether the endpoint requires a private network address. A localhost URL cannot serve a hosted remote client.
A practical rollout sequence
- List the user tasks an AI should perform and select the smallest set of read-only tools that satisfy them.
- Refactor shared business behavior into application services if REST controllers currently contain the rules.
- Pin compatible MCP package and protocol versions, register the server and map a dedicated Streamable HTTP route.
- Add authentication, tenant policies, argument validation, output redaction, rate limits and audit logging.
- Run discovery, negative, retry, timeout and authorization tests with a real client.
- Deploy behind HTTPS with health monitoring and a rollback path, then add write tools one at a time with idempotency protections.
This approach lets Claude and Gemini use capabilities your API already implements while keeping domain logic and security under your control. The MCP layer is an interface adapter; it should remain small enough to review like any other privileged API surface.
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