agent-economy-data

MCP server counts from the official registry, new servers per day, and MCP/A2A spec changes. As is.

Should I use this

Quality & Safety

B
Description quality
100%
Schema completeness
56%
Naming quality
80%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~1,135Tokens (tool definitions)
~451 BTypical response size
Moderate attention impact (0.89% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "agent-economy-data": {
      "url": "https://agent-economy-data.onrender.com/mcp"
    }
  }
}

Remote endpoints

https://agent-economy-data.onrender.com/mcpstreamable-http

What it can do

Tool inventory

Tools (7)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢ecosystem_overview

Start here: the size and recent growth of the MCP server ecosystem in one call. Returns the total number of servers in the Official MCP Registry, new servers in the last 7 and 30 days, the 3 latest MCP and A2A spec changes with source links, and the snapshot date. Good for 'How big is the MCP ecosystem and what changed lately?'. Example: ecosystem_overview() -> {total_servers, new_servers_last_7_days, new_servers_last_30_days, latest_spec_changes, snapshot_date}. No arguments.

Input Schema

{
  "type": "object",
  "properties": {},
  "title": "ecosystem_overviewArguments"
}
🟢registry_totals

A headline number for a post, slide or dashboard: how many MCP servers the Official MCP Registry lists, split by status (active, deprecated), remote transport (streamable-http, sse) and package type (npm, pypi, ...). Good for 'How many MCP servers are there, and how many run remotely?'. Example: registry_totals() -> {unique_servers, by_status, by_remote_transport, by_package_type}. No arguments.

Input Schema

{
  "type": "object",
  "properties": {},
  "title": "registry_totalsArguments"
}
🟢new_servers_count_since(date)

Growth since any date: how many MCP servers were first published on or after it, split by namespace type. Good for 'How many new MCP servers since October?'. Example: new_servers_count_since(date="2026-10-01") -> {since, count, by_namespace_type}. Date format YYYY-MM-DD. The date is optional: with no arguments it counts the last 30 days up to the snapshot date.

Input Schema

{
  "type": "object",
  "properties": {
    "date": {
      "default": "",
      "description": "Date as YYYY-MM-DD, for example \"2026-10-01\". Optional: empty means the last 30 days up to the snapshot date.",
      "examples": [
        "2026-10-01"
      ],
      "title": "Date",
      "type": "string"
    }
  },
  "title": "new_servers_count_sinceArguments"
}
🟢namespace_types

Who publishes MCP servers and how: the split between code host namespaces (io.github, io.gitlab, io.bitbucket) and publishers' own domains, by servers and by distinct namespaces. Good for 'What share of MCP servers use their own domain?'. Example: namespace_types() -> {servers_by_namespace_type, distinct_namespaces_by_type}. No arguments.

Input Schema

{
  "type": "object",
  "properties": {},
  "title": "namespace_typesArguments"
}
🟢daily_new_counts(days)

A ready-to-chart series of new MCP servers per UTC day for the last N days (1 to 365, default 30). Good for 'Show daily new MCP servers over the last two weeks'. Example: daily_new_counts(days=14) -> {series: [{date, new_servers}, ...]}. days is optional: with no arguments you get 30 days. The last day can be partial, see snapshot_at.

Input Schema

{
  "type": "object",
  "properties": {
    "days": {
      "default": 30,
      "description": "Number of days back from the snapshot date, 1 to 365. Optional, default 30.",
      "examples": [
        14
      ],
      "title": "Days",
      "type": "integer"
    }
  },
  "title": "daily_new_countsArguments"
}
🟢snapshot_info

What to cite: the snapshot date and source behind the other tools, and which fields are kept or dropped. Good for 'Which day do these numbers describe and where do they come from?'. Example: snapshot_info() -> {snapshot_at, source, fields_kept, fields_dropped}. No arguments.

Input Schema

{
  "type": "object",
  "properties": {},
  "title": "snapshot_infoArguments"
}
🟢spec_changes_since(date)

What changed in the MCP and A2A specifications since a date, each as a short summary in our own words with a link to the release notes. A short curated list, not a full changelog. Good for 'What changed in the MCP spec this year?'. Example: spec_changes_since(date="2026-01-01") -> {count, changes: [{spec, tag, date, summary, source}]}. Date format YYYY-MM-DD. The date is optional: with no arguments it starts on 1 January of the snapshot year.

Input Schema

{
  "type": "object",
  "properties": {
    "date": {
      "default": "",
      "description": "Date as YYYY-MM-DD, for example \"2026-01-01\". Optional: empty means 1 January of the snapshot year.",
      "examples": [
        "2026-01-01"
      ],
      "title": "Date",
      "type": "string"
    }
  },
  "title": "spec_changes_sinceArguments"
}

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Evidence

Recent observations

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