MCP Registry Catalogs in 2026: Official Registry vs Smithery vs mcp.so

TL;DR — Three catalog tiers exist: the Official Registry (canonical metadata, API freeze v0.1), high-volume registries like Smithery (7k+) and mcp.so (19.7k+), and curated directories like PulseMCP. Pick the Official Registry as your source of truth; use Smithery/mcp.so for breadth; trust nothing without a security review.

What the MCP server does

A registry isn't an MCP server — it's a catalog of MCP servers. Each entry has metadata: name, description, install command, transport, auth, source URL, maintainer, last-updated. Agents and IDEs use this metadata to bootstrap MCP connections without users hand-writing JSON.

flowchart LR
 A[User] -->|"add Notion MCP"| B[IDE/Client]
 B -->|search| C[Official Registry]
 C -->|metadata| B
 B -->|install command| D[Local MCP]
 E[Smithery] -->|sub-registry| C
 F[mcp.so] -->|sub-registry| C

Auth + transport (sse/stdio/http)

The Official Registry exposes a public REST API (no auth for read; OAuth for publish). Smithery, mcp.so, and PulseMCP each have their own APIs and CLIs. Many third-party registries pull from the Official Registry on a schedule and add their own metadata layer (rankings, security scans, install-counts).

How CallSphere uses it

We publish our public-facing MCPs (none yet — this is on the 2026 roadmap) to the Official Registry. We consume from all three: Official for canonical truth on official servers (Stripe, GitHub, Notion), Smithery for hosted-remote convenience, mcp.so for breadth when we're researching what exists in a domain.

For our AI Engineer skill, the registry catalogs are how the agent answers "is there an MCP for X?" — we cache the Official Registry API responses and do a fuzzy search before suggesting a server. With 115+ DB tables of internal data and 90+ tools wired to 37 specialist agents, the registry pattern is how we expand our tool surface without hand-writing every integration.

Build / install

1. Bookmark four URLs: registry.modelcontextprotocol.io, smithery.ai, mcp.so, pulsemcp.com.
2. For discovery: search the Official Registry first; cross-reference with PulseMCP for human-curated reviews.
3. For install: prefer the Official Registry's install command — it's the canonical source.
4. For hosted-remote: Smithery's CLI handles it (smithery install <server>).
5. For security: always run a third-party MCP through the Inspector before connecting to anything sensitive.
6. To publish: follow the Official Registry's quickstart — submit metadata via the publish API with OAuth.

FAQ

Which registry is canonical? registry.modelcontextprotocol.io — backed by Anthropic, GitHub, PulseMCP, Microsoft.

Smithery vs mcp.so? Smithery is curated and offers hosting; mcp.so is broader and community-submitted. Use both.

Are servers vetted? No — registry inclusion ≠ security. A March 2026 scan of 100 Smithery servers found 22 with security findings. Always review before install.

API freeze v0.1? The Official Registry committed to no breaking API changes for the foreseeable future. Build against it confidently.

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Sources

• Official MCP Registry
• MCP Registry on GitHub
• Smithery (smithery.ai)
• TrueFoundry Best MCP Registries 2026
• Composio Smithery Alternatives
• 100 MCP Servers Stress-Tested (DigitalApplied)
• Smithery Security Findings (DEV)

MCP Registry Catalogs in 2026: Official Registry vs Smithery vs mcp.so: production view

MCP Registry Catalogs in 2026: Official Registry vs Smithery vs mcp.so ultimately resolves into one engineering question: when do you use the OpenAI Realtime API versus an async pipeline? Realtime wins on latency for live calls. Async wins on cost, retries, and structured tool reliability for callbacks and SMS flows. Most teams need both, and the routing layer between them becomes the most load-bearing piece of the stack.

Serving stack tradeoffs

The big fork is managed (OpenAI Realtime, ElevenLabs Conversational AI) versus self-hosted on GPUs you operate. Managed wins on cold-start, model freshness, and zero-ops; self-hosted wins on unit economics past a certain conversation volume and on data residency for regulated verticals. CallSphere runs hybrid: Realtime for live calls, self-hosted Whisper + a hosted LLM for async, both routed through a Go gateway that enforces per-tenant rate limits.

Latency budgets are non-negotiable on voice. End-to-end target is sub-800ms ASR-to-first-token and sub-1.4s first-audio-out; anything beyond that and turn-taking feels stilted. GPU residency in the same region as your TURN servers matters more than choosing a slightly bigger model.

Observability is the unglamorous backbone — every conversation produces logs, traces, sentiment scoring, and cost attribution piped to a per-tenant dashboard. HIPAA aligned isolation keeps healthcare traffic separated from salon traffic at the storage layer, not just the API.

FAQ

Is this realistic for a small business, or is it enterprise-only? 57+ languages are supported out of the box, and the platform is HIPAA aligned, which removes most of the procurement friction in regulated verticals. For a topic like "MCP Registry Catalogs in 2026: Official Registry vs Smithery vs mcp.so", that means you're not starting from scratch — you're configuring an agent template that's already been hardened across thousands of conversations.

Which integrations have to be in place before launch? Day one is integration mapping (scheduler, CRM, messaging) and prompt tuning against your top 20 real call transcripts. Day two through five is shadow-mode running, where the agent transcribes and recommends but a human still answers, so you can compare side-by-side. Go-live is the moment your eval pass-rate clears your internal bar.

How do we measure whether it's actually working? The honest answer: it scales until your tool catalog gets stale. The agent is only as good as the integrations it can actually call, so the operational discipline is keeping schemas, webhooks, and fallback paths green. The platform handles the rest — observability, retries, multi-region routing — without your team owning the GPU layer.

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