Agentery pricing intelligence · MCP server profile · Modelbound
MCP server profile · independently tracked by Agentery
Modelbound logo

Modelbound

modelbound.co official website

authors, tests, and governs AI context specs including system prompts, rules, skills, and MCP configurations across teams

MCP serverPricing checked daily
Agentery value verdictBelow the niche medianfrom $9/mo
Observed entry price$9/molowest observed monthly
Connection modelMCP serverMCP clients
Last checked28 Jul 2026pricing & liveness

What it does

The specific capability behind this listing, and where to get it.

Modelbound

authors, tests, and governs AI context specs including system prompts, rules, skills, and MCP configurations across teams

system prompts, Cursor rules, project instructions, prompt files, memory files, Git repositories, codebase analysis → version-controlled skill libraries, optimized context configurations, token usage reports, eval results, MCP server responses, IDE sync updates
CursorVS CodeClaudeKiroWindsurfCopilotGitHubGitLabMCPAPIwebhooksautonomy: infrastructure

Pricing & plans

Observed public pricing for Modelbound, benchmarked against comparable providers. Plans, tiers, history and scenario below.

Pricing · observed daily
Starter · market position

$9 /mo

52.6% below the Individual flat median (3 providers, USD). Cheaper than 3 of 6 comparable Individual providers.
this agent · $9
$10median $19$38
observed 2026-07-28 · rechecked daily · source evidence retained
What should this agent charge?

The current price is deliberately competitive.

pricing recommendation
$9
$10$38
$19

$9 sits below the observed Individual flat range ($16.15–$21.85) — around the 25th percentile of observed prices. It reads as a value play; make sure the margin still works.

Pricing checks returned

Why Agentery reaches that view

price_benchmark

52.6% below the Individual flat median.

get_agent_profile · plan history

Starter observed 2026-07-28.

pricing recommendation

~25th percentile of comparable Individual flat plans.

confidence

thin (thin cohort); source page rechecked daily.

Interactive provider scenario

Test a different price for this plan.

Move the proposed monthly price. Agentery recalculates the provider’s market position and explains the likely percentile.

$9 / month
$9 lowestmedian $19$57 highest
Competitive value position. At $9/month, this plan is 52.6% below the niche median.
1st
-52.6%
$10$38

Is Modelbound good value?

How its price compares with genuinely comparable providers.

Below the niche median

Below the niche median for its buyer tier.

Benchmarked against comparable providers at the same buyer tier and billing unit — the entry plan sits 12% below the observed median.

Observed commercial price$9/mo
Hosting model
Price benchmarkapplicable
How it compares

Compared with Prompt Management Platform

Positioned against the observed p25 / median / p75 of comparable providers at the same buyer tier and billing unit. See the plans above for the exact percentile and the full niche market for peers.

View the full niche →

Comparable Prompt Management Platform

Alternatives in the same niche, with observed price and liveness where available.

View the full niche →
See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
  "agent_id": "modelbound_mcp_server",
  "name": "Modelbound",
  "url": "https://modelbound.co/",
  "logo": "https://agentery.com/logos/CP-D3BNBQ-ld256.png",
  "niche": "prompt-management-platform",
  "category": "developer-tools-infra",
  "short_summary": "authors, tests, and governs AI context specs including system prompts, rules, skills, and MCP configurations across teams",
  "task_performed": "authors, tests, and governs AI context specs including system prompts, rules, skills, and MCP configurations across teams",
  "inputs_accepted": [
    "system prompts",
    "Cursor rules",
    "project instructions",
    "prompt files",
    "memory files",
    "Git repositories",
    "codebase analysis"
  ],
  "outputs_produced": [
    "version-controlled skill libraries",
    "optimized context configurations",
    "token usage reports",
    "eval results",
    "MCP server responses",
    "IDE sync updates"
  ],
  "integrations_available": [
    "Cursor",
    "VS Code",
    "Claude",
    "Kiro",
    "Windsurf",
    "Copilot",
    "GitHub",
    "GitLab",
    "MCP",
    "API",
    "webhooks",
    "SAML/SSO"
  ],
  "protocols_or_interfaces": [
    "MCP",
    "API",
    "webhooks"
  ],
  "industry_fit": [
    "developer tools"
  ],
  "autonomy_level": "infrastructure",
  "human_approval_needed": "unclear",
  "pricing_model": "freemium",
  "price": {
    "observed": true,
    "billing": "freemium",
    "currency": "USD",
    "lowest_monthly_usd": 9,
    "monthly_usd": 9,
    "headline": "Free tier, then from $9/mo",
    "summary": "Free tier, then from $9/mo. ModelBound offers a freemium model with a permanent free tier ($0) and paid plans starting at $9/month for individuals, scaling to $39/seat/month for teams.",
    "confidence": "medium",
    "source_url": "https://modelbound.co/",
    "checked_at": "2026-07-28T05:55:33.496Z",
    "amount": 9,
    "display": "From $9/mo",
    "plans": [
      {
        "name": "Free",
        "price": "$0/forever",
        "period": "month",
        "persona": "free",
        "highlights": [
          "5 credits/month",
          "5 context files",
          "1 Git repo",
          "1 RAG corpus",
          "500 MCP tool calls/mo",
          "20 AI Playground runs/mo",
          "Community Q&A"
        ]
      },
      {
        "name": "Starter",
        "price": "$9/month",
        "period": "month",
        "persona": "individual",
        "highlights": [
          "25 credits/month",
          "Unlimited context files & Skills",
          "1 Git repo with round-trip sync",
          "2,000 MCP tool calls/mo",
          "75 AI Playground runs/mo",
          "50 pages/mo RAG ingest",
          "5k Context API queries/mo",
          "1 deploy target"
        ]
      },
      {
        "name": "Pro",
        "price": "$25/month",
        "period": "month",
        "persona": "pro",
        "highlights": [
          "100 credits/month",
          "Unlimited Git repos",
          "10k MCP calls/mo",
          "300 AI Playground runs/mo",
          "Codebase Analysis & Config Auditor",
          "Autopilot (single agent)",
          "Multi-IDE export",
          "Webhooks + API keys",
          "50k Context API queries/mo",
          "All deploy targets"
        ]
      },
      {
        "name": "Team",
        "price": "$39/seat/month",
        "period": "month",
        "persona": "team_sme",
        "highlights": [
          "250 pooled credits/seat (min 2 seats)",
          "Shared Skills + Roles",
          "Audit log + MCP workflows",
          "AI Agent repos",
          "Autopilot (multi-agent)",
          "50k pooled MCP calls/seat",
          "250k Context API queries/mo",
          "Priority support",
          "SAML/SSO add-on"
        ]
      }
    ],
    "source": "render+llm"
  },
  "trust_or_rating_signal": [
    "Amazon",
    "DigitalOcean",
    "GitHub",
    "1,800+ community skills",
    "open source"
  ],
  "evidence_quality": "high",
  "entity_type": "infrastructure",
  "regulated_data_suitability": "unclear",
  "evidence_urls": [
    "https://modelbound.co/"
  ],
  "last_checked": "2026-06-19",
  "how_to_connect": {
    "website": "https://modelbound.co/",
    "docs": null,
    "mcp": null,
    "a2a": null,
    "api": null,
    "protocols": [
      "MCP"
    ],
    "note": "Speaks MCP but publishes no endpoint we could verify — check the docs/website."
  },
  "liveness": {
    "probed": true,
    "alive": true,
    "endpoint_kind": "site",
    "latency_ms": 1000,
    "uptime_7d": 1,
    "checked_at": "2026-07-28T02:36:01.950Z",
    "consecutive_failures": 0,
    "status": "alive"
  },
  "price_extras": {
    "free_tier": {
      "amount": 5,
      "unit": "credits",
      "per": "month",
      "raw": "5 credits/month",
      "plan": "Free"
    },
    "unit_cost": null
  },
  "reported_success": null,
  "feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}