servers vs apify-mcp-server
Two of the top projects in MCP servers, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
servers
Reference MCP servers for files, git, fetch, memory and time
apify-mcp-server
Official MCP server exposing Apify Store Actors as tools for web scraping
Verdict
servers ranks higher, 94 to 86. Of the 4 score parts we measure for both, servers leads on 2, apify-mcp-server on 1 and 1 is even.
- Adoptionservers leads by 25 points, 98 to 73: a wide gap.
- FreshnessEven at 100.
- Maintenanceservers leads by 15 points, 99 to 84: a wide gap.
- Agent-readyapify-mcp-server leads by 40 points, 85 to 45: a wide gap.
Pick servers if you are
Developers learning MCP or wiring basic tools into an MCP client
- Maintained by the MCP steering group, so it tracks the spec and official SDKs
- Seven small servers covering files, git, web fetch, knowledge-graph memory and time
Pick apify-mcp-server if you are
Agent builders who need web scraping and data extraction tools over MCP
- One connection reaches thousands of Store Actors instead of a separate MCP server per site
- Tool categories selectable via `tools` URL parameter, `--tools` flag or `TOOLS` env var
| What we compare | servers | apify-mcp-server |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 98, widely used | 73, popular |
| Momentum | Not scored for this kind | Not scored for this kind |
| Freshness | 100, active | 100, active |
| Maintenance | 99, healthy | 84, healthy |
| Agent-ready | 45, minimal | 85, ready |
| Facts from GitHub and the README | ||
| Stars | 91.9k | 15.7k |
| License | custom license (read the license) | MIT (permissive) |
| Last commit | Nov 2026 | Nov 2026 |
| Last release | Nov 2026 | Nov 2026 |
| Language | TypeScript | TypeScript |
| Docker | No | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Not stated |
servers
Official collection of reference Model Context Protocol servers maintained by the MCP steering group: Everything, Fetch, Filesystem, Git, Memory, Sequential Thinking and Time. TypeScript servers start with npx and Python ones with uvx or pip. All serve stdio; only Everything also serves Streamable HTTP. The README states they are educational examples, not production-ready.
Who it is for: Developers learning MCP or wiring basic tools into an MCP client
Strengths
- Maintained by the MCP steering group, so it tracks the spec and official SDKs
- Seven small servers covering files, git, web fetch, knowledge-graph memory and time
- Starts with one command: npx for TypeScript servers, uvx or pip for Python ones
- Everything server exercises prompts, resources and tools, and also serves Streamable HTTP
Weaknesses
- README says these are reference implementations, not production-ready
- Only Everything supports Streamable HTTP; the other servers are stdio only
- Many earlier servers (GitHub, Postgres, Slack, Redis and others) are archived
- License is reported as NOASSERTION: Apache-2.0 for new contributions, MIT for older code
- no GPU
- Needs Node.js (npx), uv or pip (Python servers), MCP client
apify-mcp-server
MCP server that lets an agent search Apify Store, read an Actor's input schema and pricing, run it, and fetch results from its dataset. It runs hosted at mcp.apify.com over Streamable HTTP with OAuth or a bearer token, or locally over stdio via the @apify/actors-mcp-server npm package. Actors execute on the Apify platform in both modes.
Who it is for: Agent builders who need web scraping and data extraction tools over MCP
Strengths
- One connection reaches thousands of Store Actors instead of a separate MCP server per site
- Tool categories selectable via `tools` URL parameter, `--tools` flag or `TOOLS` env var
- Hosted OAuth endpoint plus local stdio mode and an .mcpb bundle for supported clients
- Also covers Actor builds, schedules, tasks, storage and Apify API access as opt-in tools
Weaknesses
- Requires an Apify account; Actors run and store results on Apify's platform, not locally
- Actor runs are paid per Actor pricing; cost depends on each Actor
- call-actor waits only 30 seconds by default, up to 45; longer runs need polling
- Local stdio mode lacks inferred output schemas for Actor results
- no GPU
- Docker
- Needs Apify account and API token or OAuth, Apify platform (Actors), Node.js 22+ for local stdio
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