# MCP Server Discovery & Ranker (`heliotrope_partridge/mcp-server-discovery`) Actor Search 7,000+ MCP (Model Context Protocol) servers on GitHub. Filter by language, category, freshness. Returns ranked list with composite relevance score (stars + recency + name match) so you find production-ready servers, not stale demos. - **URL**: https://apify.com/heliotrope\_partridge/mcp-server-discovery.md - **Developed by:** [Roberto Espino](https://apify.com/heliotrope_partridge) (community) - **Categories:** AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## MCP Server Discovery & Ranker **Find the right Model Context Protocol server in seconds, not hours.** The MCP ecosystem has 7,000+ public servers and is growing weekly. Bare GitHub search ranks them by stars — but a 5,000-star server last touched 14 months ago is probably dead, and a 200-star server pushed yesterday might be exactly what you need. This actor surfaces the right tradeoff. ### What it does Searches every MCP server tagged on GitHub (`topic:model-context-protocol`, with `topic:mcp-server` fallback), filters by language and freshness, and returns a ranked list with a composite relevance score. One API call, structured output, no scraping. ### When to use it - You're building an AI agent and need a tool integration (database, GitHub, filesystem, browser, etc.) — search by topic keyword - You're auditing the MCP ecosystem for trends — leave query empty for top-overall - You want only TypeScript servers (or Python, Rust, Go, Java, C#) — set the `language` filter - You want only actively-maintained servers — drop `freshDays` to 30 or 60 ### Input | Field | Type | Default | Notes | |-------|------|---------|-------| | `query` | string | `""` | Topic keyword, e.g. `"database"`, `"github"`, `"filesystem"`, `"browser"`. Empty = top overall. | | `language` | enum | `""` | `typescript`, `javascript`, `python`, `rust`, `go`, `java`, `csharp`. Empty = any. | | `freshDays` | int | `90` | Only servers pushed-to in the last N days. `0` = no filter. | | `limit` | int | `25` | Max results, 1–100. | | `githubToken` | secret | `""` | Optional GitHub PAT — raises rate limit from 60 to 5,000 req/hr. | ### Output One dataset record per ranked server: ```json { "name": "fastmcp", "full_name": "PrefectHQ/fastmcp", "html_url": "https://github.com/PrefectHQ/fastmcp", "description": "A fast, Pythonic way to build MCP servers and clients.", "language": "Python", "stars": 24651, "forks": 1234, "open_issues": 56, "pushed_at": "2026-04-18T...", "topics": ["mcp", "model-context-protocol", "..."], "license": "MIT", "score": 0.7421 } ```` ### Scoring `score = 0.5 × log10(stars)/5 + 0.3 × freshness(0–1) + 0.2 × query_match` - **Stars (50%)** — log-scaled so 5k→50k matters less than 50→500. - **Freshness (30%)** — linear decay over 365 days; this-week ≈ 1.0, dead-after-a-year = 0. - **Query match (20%)** — name + description substring against your query. A 200-star server pushed 90 days ago beats a 10k-star server pushed 2 years ago. That's intentional. ### Example runs **Find a database MCP in TypeScript, fresh:** ```json { "query": "database", "language": "typescript", "freshDays": 90, "limit": 10 } ``` **Top 5 MCP servers across the whole ecosystem:** ```json { "limit": 5 } ``` **All Rust MCP servers, no freshness filter:** ```json { "language": "rust", "freshDays": 0, "limit": 50 } ``` ### Limitations - Relies on GitHub topic tagging. Servers that don't tag `mcp` / `model-context-protocol` / `mcp-server` won't appear. - Lexical match only — no semantic search. Use `query` as a coarse keyword filter. - Anonymous use is rate-limited (60 req/hr per IP). For production, supply a `githubToken`. - Scoring is opinionated. If you'd weight freshness or stars differently, fork it. ### License Apache-2.0. Source: see Apify Console for the latest version. # Actor input Schema ## `query` (type: `string`): Topic or keyword to filter MCP servers. Examples: 'database', 'github', 'filesystem', 'browser'. Leave empty to get top-ranked overall. ## `language` (type: `string`): Filter by primary language (e.g. typescript, python, rust, go). Empty = any. ## `freshDays` (type: `integer`): Only include servers pushed-to within the last N days. 0 = no filter. ## `limit` (type: `integer`): Number of ranked results to return (1-100). ## `githubToken` (type: `string`): Optional GitHub personal access token to lift rate limits (60->5000 req/hr). Leave empty for anonymous. ## Actor input object example ```json { "query": "", "language": "", "freshDays": 90, "limit": 25 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("heliotrope_partridge/mcp-server-discovery").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("heliotrope_partridge/mcp-server-discovery").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call heliotrope_partridge/mcp-server-discovery --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=heliotrope_partridge/mcp-server-discovery", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MCP Server Discovery & Ranker", "description": "Search 7,000+ MCP (Model Context Protocol) servers on GitHub. Filter by language, category, freshness. Returns ranked list with composite relevance score (stars + recency + name match) so you find production-ready servers, not stale demos.", "version": "0.1", "x-build-id": "MKviHaALH1vD689Yh" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/heliotrope_partridge~mcp-server-discovery/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-heliotrope_partridge-mcp-server-discovery", "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/heliotrope_partridge~mcp-server-discovery/runs": { "post": { "operationId": "runs-sync-heliotrope_partridge-mcp-server-discovery", "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/heliotrope_partridge~mcp-server-discovery/run-sync": { "post": { "operationId": "run-sync-heliotrope_partridge-mcp-server-discovery", "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", "properties": { "query": { "title": "Query", "type": "string", "description": "Topic or keyword to filter MCP servers. Examples: 'database', 'github', 'filesystem', 'browser'. Leave empty to get top-ranked overall.", "default": "" }, "language": { "title": "Language filter", "enum": [ "", "typescript", "javascript", "python", "rust", "go", "java", "csharp" ], "type": "string", "description": "Filter by primary language (e.g. typescript, python, rust, go). Empty = any.", "default": "" }, "freshDays": { "title": "Freshness window", "minimum": 0, "maximum": 3650, "type": "integer", "description": "Only include servers pushed-to within the last N days. 0 = no filter.", "default": 90 }, "limit": { "title": "Max results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Number of ranked results to return (1-100).", "default": 25 }, "githubToken": { "title": "GitHub token (optional)", "type": "string", "description": "Optional GitHub personal access token to lift rate limits (60->5000 req/hr). Leave empty for anonymous." } } }, "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 } } } } } } } } } } ```