Tester MCP Client
Pricing
Pay per event
Go to Store
Tester MCP Client
A model context protocol (MCP) client that connects to any MCP server using Server-Sent Events (SSE) and displays the conversation in a chat-like UI. It is a standalone Actor server designed for testing MCP servers over SSE.
4.8 (5)
Pricing
Pay per event
14
Total users
414
Monthly users
166
Runs succeeded
0%
Last modified
7 hours ago
You can access the Tester MCP Client programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.1", "x-build-id": "MxtVz4BVppTYJiVIb" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jiri.spilka~tester-mcp-client/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jiri.spilka-tester-mcp-client", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jiri.spilka~tester-mcp-client/runs": { "post": { "operationId": "runs-sync-jiri.spilka-tester-mcp-client", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jiri.spilka~tester-mcp-client/run-sync": { "post": { "operationId": "run-sync-jiri.spilka-tester-mcp-client", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mcpUrl", "modelName" ], "properties": { "mcpSseUrl": { "title": "MCP Server Sent Events (SSE) URL", "type": "string", "description": "MCP Server Sent Events (SSE) URL for receiving updates from the server.\n\nMake sure that URL path ends with `/sse`" }, "mcpUrl": { "title": "MCP Server URL", "type": "string", "description": "URL of the MCP Server for updates. Use `SSEClientTransport` if the URL ends with `/sse`; otherwise, use `HttpStreamableClientTransport`.", "default": "https://mcp.apify.com/sse?enableAddingActors=true" }, "mcpTransportType": { "title": "MCP transport type specification", "enum": [ "sse", "http-streamable-json-response" ], "type": "string", "description": "This setting helps you to override the MCP transport layer if required. Use `SSEClientTransport` for Server Sent Events (2024-11-05) or `HttpStreamableClientTransport` for JSON Response Streamable HTTP (2025-03-26).", "default": "sse" }, "headers": { "title": "HTTP headers", "type": "object", "description": "HTTP headers to be sent with the request to the MCP server. If you are using Apify's MCP server, headers are NOT required" }, "systemPrompt": { "title": "System prompt", "type": "string", "description": "System prompt for the Claude model", "default": "You are a helpful Apify assistant with tools called Actors.\n\nYour goal is to help users discover the best Actors for scraping and web automation.\nYou have access to a list of tools that can help you discover Actors, find details, and include them among tools for later execution.\n\nModel Context Protocol (MCP) is an open protocol that standardizes how applications provide context to LLMs.\n\nChoose the appropriate Actor based on the conversation context. If no Actor is needed, reply directly.\n\nPrefer Actors with more users, stars, and runs.\nWhen you need to use an Actor, explain how it is used and with which parameters.\nNever call an Actor unless it is required by the user!\nAfter receiving an Actor's response:\n1. Transform the raw data into a natural, conversational response.\n2. Keep responses concise but informative.\n3. Focus on the most relevant information.\n4. Use appropriate context from the user's question.\n5. Avoid simply repeating the raw data.\nAlways use 'Actor', not 'actor'. Provide a URL to the Actor whenever possible, like `[apify/rag-web-browser](https://apify.com/apify/rag-web-browser)`.\nActor execution may take some time, and results can be large. Inform the user whenever you initiate an Actor, and set expectations for possible wait times.\nIf possible, limit the number of results to 3, 5, or 10. Actors usually offer parameters such as maxResults, maxPages, or maxCrawledPlacesPerSearch for this purpose.\nThe server limits the number of results returned, but you can always request more results from paginated datasets or fetch additional data from the key-value store if needed.\n" }, "modelName": { "title": "Anthropic Claude model (Anthropic is only supported provider now)", "enum": [ "claude-sonnet-4-0", "claude-3-7-sonnet-latest", "claude-3-5-haiku-latest" ], "type": "string", "description": "Select a model to be used for selecting tools and generating text.\n\n- Claude Sonnet 4 - the most intelligent model\n- Claude 3.7 Sonnet - highly intelligent model\n- Claude 3.5 Haiku - a fastest model", "default": "claude-3-5-haiku-latest" }, "llmProviderApiKey": { "title": "LLM Provider API key (Anthropic is only supported provider now)", "type": "string", "description": "API key for accessing a Large Language Model. If you provide your own API key, Actor will not charge for query answered event." }, "modelMaxOutputTokens": { "title": "Maximum tokens for Claude response", "maximum": 10000, "type": "integer", "description": "Maximum number of tokens in the Claude response. The higher the number, the longer the response time", "default": 2048 }, "maxNumberOfToolCallsPerQuery": { "title": "Maximum number of tool calls per query", "type": "integer", "description": "Maximum number of times a tool can be called with one query. Keep this number low for simple flows", "default": 20 }, "toolCallTimeoutSec": { "title": "Tool call timeout", "type": "integer", "description": "Timeout for a single tool call in seconds", "default": 300 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } }}Tester MCP Client OpenAPI definition
OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Tester MCP Client from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients:
