Apiany MCP vs ModelRunner
A side-by-side look at the Apiany MCP and ModelRunner MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Apiany MCP for finance & fintech work as a local process; choose ModelRunner for finance & fintech over a hosted endpoint. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Apiany MCP when
- You need dedicated capabilities in the Finance & Fintech domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
APIANY_BASE_URL, APIANY_API_KEY. - You want tools like
list_models, search_models, get_model.
Choose ModelRunner when
- You need dedicated capabilities in the Finance & Fintech domain.
- You prefer a remote HTTP/SSE transport.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Finance & Fintech | Finance & Fintech |
| Quality signal | 59/100 · Good | 37/100 · Fair |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Remote HTTP/SSE |
| Auth | API key required | Not declared |
| Pricing | Not declared | Not declared |
| Required env vars | APIANY_BASE_URLAPIANY_API_KEY | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 0 |
| Directory activity | 5 views 0 installs 0 upvotes | 0 views 0 installs 0 upvotes |
| Tools | 10 | Not listed |
| Full listing | View Apiany MCP | View ModelRunner |
Tools & capabilities
Apiany MCP tools 10
list_modelsList public APIAny models with pricing and capability metadata.search_modelsSearch APIAny models by natural-language text, provider, modality, or capability.get_modelGet one APIAny model by public model id or display name.estimate_costEstimate APIAny credits for a model using public pricing metadata.get_integration_examplesReturn APIAny integration examples for a model and language.get_model_usageReturn endpoint, payload, async behavior, and language example for one or more APIAny models.create_image_taskCreate a paid APIAny asynchronous image generation task. Requires APIANY_API_KEY and confirm_paid_request=true.create_video_taskCreate a paid APIAny asynchronous video generation task. Requires APIANY_API_KEY and confirm_paid_request=true.get_task_statusGet an APIAny async generation task status. Requires APIANY_API_KEY.get_docs_contextReturn compact APIAny documentation context from llms.txt.
ModelRunner tools
No tool names declared yet. Check the project README from the listing page.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Apiany MCP
{
"mcpServers": {
"apiany-mcp": {
"command": "npx",
"args": [
"-y",
"@apiany-ai/mcp"
],
"env": {
"APIANY_BASE_URL": "YOUR_APIANY_BASE_URL_HERE",
"APIANY_API_KEY": "YOUR_APIANY_API_KEY_HERE"
}
}
}
}
ModelRunner
{
"mcpServers": {
"modelrunner": {
"url": "https://mcp.modelrunner.run/mcp"
}
}
}
Frequently asked questions
Apiany MCP is categorized under Finance & Fintech and uses a local stdio subprocess. ModelRunner belongs to Finance & Fintech and uses a remote HTTP/SSE transport. Pick Apiany MCP for finance & fintech work and ModelRunner for finance & fintech.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Apiany MCP has no declared pricing — check the project's own site. Auth: api key required. ModelRunner has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add apiany-mcp and modelrunner as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Apiany MCP has a quality signal of 59/100 (Good) with 5 views, 0 installs and 0 GitHub stars. ModelRunner has 37/100 (Fair) with 0 views, 0 installs and 0 GitHub stars.