# mcp.so vs Scale

mcp.so records 286,704 monthly visits with -3% month-over-month growth and Free pricing. Scale records 616,915 monthly visits with +12.5% growth and Contact for Pricing pricing.

| Metric | [mcp.so](https://openaitools.app/tool/mcp-server) | [Scale](https://openaitools.app/tool/scale) |
| :--- | :--- | :--- |
| Website URL | https://mcp.so | https://scale.com |
| Categories | AI Tools Directory, Large Language Models (LLMs), AI Developer Tools | AI Developer Tools, Large Language Models (LLMs), AI Models, AI Agent |
| Pricing Model | Free | Contact for Pricing |
| Monthly Visits | 286,704 | 616,915 |
| MoM Growth Rate | -3% | +12.5% |
| Primary Market | United States | United States |
| Direct Visits | 107,648 | 191,408 |
| Review Score | 4.2 | 4.7 |
| Saved Count | 0 | 3 |
| Supported Platforms | Website | Website |

## mcp.so

mcp.so organises the fast-growing Model Context Protocol ecosystem in one searchable place. You can browse servers by category (developer tools, AI and agents, cloud infrastructure, memory and knowledge, media and design), inspect remote endpoints, and read setup details before wiring a server into Claude, Cursor or another MCP-compatible client. Featured and trending sections surface popular or newly added servers, and rankings help you gauge what the community is adopting.

Beyond raw server listings, the site collects MCP clients (apps, IDEs and frameworks that speak the protocol), official CLI tools such as Bun, Cloudflare Wrangler, DuckDB and FFmpeg, reusable agent loops and skills, and curated collections. A feed tracks new arrivals, and submit/claim flows let maintainers add or take ownership of their own listings.

For anyone building with AI agents, mcp.so works as a discovery and reference layer: pick a capability, check how the server connects and authenticates, follow the setup guide, and keep an eye on what the community is installing each week. It is a directory, so it does not itself host or run the servers it lists.

**Pricing & Plans:** Free to browse and use the directory. Advertising, featured placement and claiming listings are handled through the site; no subscription is required for normal browsing.

- **Searchable MCP server directory:** Find servers by name, category, tag, runtime or integration, with featured, trending and newest sections that track community activity.
- **Remote endpoints and setup guides:** Review hosted MCP endpoints, authentication requirements and per-client setup instructions before you connect anything.
- **Clients, CLI tools and skills:** Discover MCP-compatible clients, official command-line tools, agent loops and reusable Claude/Codex skills in dedicated sections.
- **Submit and claim listings:** Maintainers can publish new servers and claim existing listings so entries stay accurate and attributable.
- **Categories, rankings and feed:** Browse top categories, compare curated selections and follow a live feed of newly added servers, tools and skills.

**Strengths:** Broad, regularly updated coverage of MCP servers and clients; Setup and authentication details gathered together in one place; Free to use with no account needed for browsing; Includes CLI tools, agent skills and curated collections beyond raw listings

**Limitations:** Listings are community-submitted, so quality and freshness can vary; It is a directory only, not a place to run or host MCP servers; Ad and featured placements can push less relevant results higher

[Profile (Markdown)](https://openaitools.app/tool/mcp-server.md)

## Scale

Scale positions itself as the infrastructure layer for reliable AI - the data, evaluations and deployment support that sit underneath working systems rather than a single consumer-facing model. Founded in 2016, it built its reputation supplying training data and labelling capacity to the autonomous vehicle and then the generative AI wave, and now describes itself as powering a large share of the world's leading generative AI model builders.

The offering spans three broad areas. Data covers sourcing and expert annotation for training and fine-tuning, including RLHF-style preference data. Evaluation covers public leaderboards and private benchmarks used to measure model capability and safety. Applications covers the build-and-deploy side: identifying a viable use case, constructing the system and owning the outcome, with agentic AI for enterprise operations.

Scale's customer list leans heavily enterprise and public sector, including large technology companies, healthcare providers, media organisations, energy companies and government defence programmes. Because engagements are scoped rather than self-serve, pricing is arranged through a sales process, and the platform is aimed at organisations with serious data volume, strict compliance needs and a mandate to put AI into production.

**Pricing & Plans:** Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity.

- **Data Engine:** Human-sourced and expert-annotated training data, including specialist contributors with advanced degrees, at the quality bar frontier labs require.
- **Model evaluation & benchmarks:** Public leaderboards plus private benchmarks that test model capability and safety for the most ambitious AI developers.
- **Enterprise AI applications:** Platform and services teams that pick the right use case, build the system and take ownership of the outcome.
- **Agentic deployment:** Agentic systems designed around measurable business outcomes across private equity portfolios, energy and healthcare operations.
- **Domain expertise:** Programmes spanning healthcare, robotics, defence, public sector and enterprise with human oversight built in.

**Strengths:** Backed by a long track record in training data and model evaluation.; End-to-end coverage from data sourcing through to deployed systems.; Experienced with regulated, classified and safety-critical environments.; Benchmarks and leaderboards give an independent view of model capability.

**Limitations:** No public pricing or self-serve signup - you need a sales conversation to get started.; Enterprise-scale contracting and data operations require real internal commitment.; Overkill for small teams with modest data or evaluation needs.; Some projects involve sensitive government and defence work with strict compliance overhead.

[Profile (Markdown)](https://openaitools.app/tool/scale.md)

## Frequently Asked Questions

### How do mcp.so and Scale compare in monthly traffic?

mcp.so has 286,704 monthly visits, while Scale has 616,915. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

mcp.so has a month-over-month growth rate of -3%; Scale has +12.5%.

### How does pricing compare?

mcp.so: Free. Free to browse and use the directory. Advertising, featured placement and claiming listings are handled through the site; no subscription is required for normal browsing. Scale: Contact for Pricing. Contact for pricing. Scale does not publish rates; engagements are scoped through a sales conversation and depend on data volume, services and programme complexity.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | +6.6% | Freemium, Contact for Pricing | Streamlines computer vision dataset annotation and model training, but is less suited for general LLM text tasks. | [.md](https://openaitools.app/tool/roboflow.md) |
| 2 | [Labelbox](https://openaitools.app/tool/labelbox) | 762,803 | -22.8% | Contact for Pricing | Focuses heavily on enterprise data labeling and training data curation, similar to Scale's core annotation business. | [.md](https://openaitools.app/tool/labelbox.md) |
| 3 | [Dang.ai](https://openaitools.app/tool/dang-ai) | 552,907 | +17.5% | Free | Curated directory and search engine cataloging thousands of general AI products rather than MCP developer integrations. | [.md](https://openaitools.app/tool/dang-ai.md) |
| 4 | [Futurepedia](https://openaitools.app/tool/futurepedia-find-the-best-ai-tools-software) | 527,719 | +22.5% | Free | Massive general AI tools directory, offering broader software discovery but less focus on specific MCP servers. | [.md](https://openaitools.app/tool/futurepedia-find-the-best-ai-tools-software.md) |
| 5 | [SkillsMP — Agent Skills Marketplace](https://openaitools.app/tool/agent-skills-marketplace) | 470,744 | -3.7% | Free | Independent public directory indexing open-source agent skill files and MCP integrations for AI developers. | [.md](https://openaitools.app/tool/agent-skills-marketplace.md) |
| 6 | [SuperAnnotate](https://openaitools.app/tool/super-annotate) | 386,034 | +37.4% | Free Trial, Contact for Pricing | Provides enterprise multimodal annotation and data management tools, but with less emphasis on managed labeling workforces. | [.md](https://openaitools.app/tool/super-annotate.md) |
| 7 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Track, evaluate, and ship AI models and agents in one connected environment. | [.md](https://openaitools.app/tool/prompts.md) |
| 8 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Focuses on post-deployment LLM observability and evaluation rather than training data generation or annotation. | [.md](https://openaitools.app/tool/arize-com.md) |
| 9 | [Encord](https://openaitools.app/tool/encord-com) | 244,204 | +9.4% | Contact for Pricing | Specializes in data infrastructure and annotation specifically tailored for computer vision and physical AI workloads. | [.md](https://openaitools.app/tool/encord-com.md) |
| 10 | [Stork](https://openaitools.app/tool/stork) | 201,544 | +2.3% | Free | Developer-focused AI tools directory and pricing tracker, though less dedicated to community-contributed MCP server lists. | [.md](https://openaitools.app/tool/stork.md) |

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Source: https://openaitools.app/compare/mcp-server-vs-scale

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)