Copilot Studio vs Relay
A side-by-side look at the Copilot Studio and Relay MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
C
Copilot StudioConversational AI · Local subprocess (stdio)MCP bridge for Copilot Studio sign-in, environment selection, and Agentic Builder access.59GoodAuth: oauth 2.0Verdict: choose Copilot Studio for conversational ai work as a local process; choose Relay for conversational ai as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
CChoose Copilot Studio when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: OAuth 2.0.
- You want tools like
discover_resources, get_consumption, manage_agents.
Choose Relay when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
RELAY_API_KEY, RELAY_BASE_URL. - You want tools like
search_models, get_model, get_pricing.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | C Copilot Studio | |
|---|---|---|
| Category | Conversational AI | Conversational AI |
| Quality signal | 59/100 · Good | 61/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | OAuth 2.0 | Not declared |
| Pricing | Not declared | Not declared |
| Required env vars | None listed | RELAY_API_KEYRELAY_BASE_URL |
| Verified owner | Community listing | Community listing |
| GitHub stars | 3 | 0 |
| Directory activity | 0 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 5 | 14 |
| Full listing | View Copilot Studio | View Relay |
Tools & capabilities
Copilot Studio tools 5
discover_resourcesDiscover connector operations and schemas, existing connections, dependent parameter values, and attachable resources.get_consumptionRead historical agent or workflow credit consumption, or current environment credit capacity.manage_agentsManage agent inventory, complete draft authoring, lifecycle, published-agent sharing, saved-draft previews, and agent evaluation suites and runs.manage_workflowsManage workflow inventory, complete draft authoring, lifecycle, real tests, and run diagnostics.get_copilot_studio_skillsStart here for Copilot Studio guidance. Read the matching core skill before authoring, then read `schema.json`.
Relay tools 14
search_modelsLists Relay models by tag and/or text. Common tags: text-to-image, image-to-image, text-to-video, image-to-video, video-to-video, text-to-speech, speech-to-text, text-to-text, text-to-embedding. image-to-image also lists every image model that takes an input image. Returns name, tag, route and accepts (input media the model takes, e.g. ["image"]; [] for none) per model (at most 50). Then call get_model with a name for its input schema.get_modelReturns one model's route, request_schema (what run_model's input must follow), request_example, pricing and availability. Then call run_model with an input shaped like request_example.get_pricingReturns Relay's public list prices (USD), optionally for one model, plus media_storage: the per-file fees of the store_output / upload retention SKUs (relay1d, relay7d, …). Then estimate_cost for a number.estimate_costEstimates the USD cost of a call from the public price list: an estimate, not an invoice (the bill uses provider-reported usage and any custom pricing on your account). Pass only the usage fields the model's billing_type (see get_model or get_pricing) reads: per_token: input_tokens, output_tokens, cached_input_tokens; per_image: image_count, resolution_tier; per_second_video: duration_seconds, quality_mode, sound; per_second_audio: duration_seconds; per_character: character_count; per_media_token: media_input_tokens, media_output_tokens. Add store_output / retention / file_count for storage fees.run_modelRuns any Relay model by name (billed to your key). input follows get_model's request_schema (request_example runs as is). Every model whose schema takes async (image, video, audio) is submitted as a task: it waits up to 45 s, past that it returns a task_id — do not resubmit, call check_task. Chat models answer inline. Result links expire 1 h after completion unless store_output names a media_storage SKU from get_pricing. Pass an idempotency_key if you may retry the same submit. Needs a Relay credential.check_taskChecks a task run_model returned (no key needed: the task_id is the capability). Waits up to 30 s for it to finish; returns the result when completed, else its status: then call check_task again, never resubmit. Task results are kept 1 h after they finish.upload_fileHosts an image, video or audio file on Relay and returns its url: pass that url to any *_url input of run_model. Give exactly one of path (local server only, ≤ 100 MB), base64 (≤ 4 MB) or url (a public link Relay copies). retention: relay1h (default, free within a daily quota) or a media_storage SKU from get_pricing. Needs a Relay credential.list_workflowsList Relay's workflow templates: multi-step pipelines (e.g. script → voiceover) run as one call. Each entry has workflow_id, input_schema and its steps (step_id + model). Run one with run_workflow; inputs follow input_schema.run_workflowStart a workflow run (one submit) and wait up to wait_seconds (≤ 45) for it to finish. Completed → the final output; still running → run_id: call check_workflow_run with it, never resubmit (a new run bills again). Each step is billed as an ordinary request. webhook_url gets ONE signed workflow.completed / workflow.failed delivery when the run ends. Get workflow_id and the inputs shape from list_workflows. Needs a Relay credential.check_workflow_runPoll a workflow run by run_id, waiting up to wait_seconds (≤ 30) for it to end. Completed → the final output; failed / cancelled → the error; still running → its steps so far: call check_workflow_run again. No key needed: the run_id is the access token.cancel_workflow_runCancel a workflow run. Cancels between steps only: a step already running completes and bills. A run that has already ended answers WORKFLOW_RUN_NOT_CANCELLABLE. Needs a Relay credential.get_creditsRead the account's credit balance, active promo credits and consumption. Needs a dashboard JWT or a custom-tier superkey; a plain inference key gets PERMISSION_DENIED (403). Needs a Relay credential.- +2 more on 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.
Copilot Studio
{
"mcpServers": {
"copilot-studio": {
"command": "npx",
"args": [
"-y",
"@microsoft/copilot-studio-mcp@latest"
]
}
}
}
Relay
{
"mcpServers": {
"relay-4": {
"command": "npx",
"args": [
"-y",
"@relaygpu/mcp"
],
"env": {
"RELAY_API_KEY": "YOUR_RELAY_API_KEY_HERE",
"RELAY_BASE_URL": "YOUR_RELAY_BASE_URL_HERE"
}
}
}
}
Frequently asked questions
Copilot Studio is categorized under Conversational AI and uses a local stdio subprocess. Relay belongs to Conversational AI and uses a local stdio subprocess. Pick Copilot Studio for conversational ai work and Relay for conversational ai.
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.
Copilot Studio has no declared pricing — check the project's own site. Auth: oauth 2.0. Relay 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 copilot-studio and relay-4 as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Copilot Studio has a quality signal of 59/100 (Good) with 0 views, 0 installs and 3 GitHub stars. Relay has 61/100 (Good) with 1 views, 0 installs and 0 GitHub stars.