keploy

Keploy MCP lets AI agents generate, run, analyze, and manage API tests and test data through natural-language commands.

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What it can do

  • Devloop Begin Oauth Install: Start the Path B agent-walked install for the V1 flow. Returns a playbook the AI walks with the dev to land a kep_* PAT in their editor's MCP config. Current implementatio
  • Devloop Setup Instructions: Return the V1 "user maintains the flow" install guide — covers Path A (clipboard one-liner), Path B (agent-walked OAuth), and the keploy/api-tests/ on-disk layout V1 create
  • Get Auth Status: Check whether the current MCP session has a valid-looking Keploy PAT attached. Returns { authenticated, auth_header_present, hint }. Useful as a first step for an agent to decide whet

What data it sees

Do you need an account

An API key from the service settings is required

Keploy MCP lets AI agents generate, run, analyze, and manage API tests and test data through natural-language commands. In short, it brings API testing and record replay testing capabilities into AI/LLM workflows.

How to connect

How to connect keploy to Claude

The server address to paste into Claude settings:

https://keploy--keploy.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect keploy to ChatGPT

The server address to paste into ChatGPT settings:

https://keploy--keploy.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect keploy to Cursor

The server address to paste into Cursor settings:

https://keploy--keploy.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (7)

Raw names from tools/list. Only developers need these.

devloop_begin_oauth_installStart the Path B agent-walked install for the V1 flow. Returns a playbook the AI walks with the dev to land a kep_* PAT in their editor's MCP config. Current implementation routes through app.keploy.io/settings/api-keys (the existing PAT-issuance surface). The full auto-provision OAuth round-trip (browser OAuth → /auth/temp-code/exchange → /user/mcp/provision → PAT auto-pasted) lands when the enterprise-ui /auth/cli-install page is built; this tool's interface won't change when that lifts, only the underlying steps will get shorter. ABSOLUTE: this tool surfaces a public URL. Do NOT print API keys, PATs, or OAuth tokens to the conversation. The dev pastes the secret into their editor config directly; the agent never sees it.
devloop_setup_instructionsReturn the V1 "user maintains the flow" install guide — covers Path A (clipboard one-liner), Path B (agent-walked OAuth), and the keploy/api-tests/ on-disk layout V1 creates. Safe to call without authentication; call this when the dev asks 'how do I add Keploy to this repo?' or when a devloop_* tool returns missing-API-key.
get_auth_statusCheck whether the current MCP session has a valid-looking Keploy PAT attached. Returns { authenticated, auth_header_present, hint }. Useful as a first step for an agent to decide whether to call other tools or show setup instructions — differentiates 'no header at all' from 'header present but wrong prefix / unsupported format'.
get_setup_instructionsReturn step-by-step instructions for connecting this MCP server to Cursor, Windsurf, VS Code, Claude Desktop, Claude Code, or Trae. Safe to call without authentication — use this when the user asks 'how do I set up Keploy MCP?' or when a tool call fails with an auth error.
get_tool_schemaFetch the exact schema(s) for tool(s) you ALREADY know by name — e.g. names a skill/playbook gave you (getTestReportFull, updateTestCase, listTestReports, getMock, getTestCase, getApp, listApps, ...). Returns ONLY the named tools: no fuzzy matching, no unrelated tools. Use this instead of search_tools whenever you know the name — it is exact and cheap. Use search_tools only to DISCOVER names you do not already know. Returns {"tools": [{name, description, inputSchema}, ...], "not_found": [names...]}.
invoke_toolRun any Keploy tool by name. Most tools are hidden from the default list. Know the name from a skill? get its schema with get_tool_schema; don't know the name? discover it with search_tools. Then call invoke_tool with that name and an "arguments" object matching the tool's inputSchema. Example: invoke_tool {"name": "getTestReportFull", "arguments": {"appId": "...", "testRunId": "...", "fields": ["status"]}}
search_toolsDISCOVER tool names you do NOT already know, by keyword. Most Keploy tools are hidden from the default tool list to save context. If you ALREADY know the exact name (e.g. a skill named it), call get_tool_schema instead — it is exact and far cheaper than this fuzzy search. Returns {"matches": [{name, description, inputSchema}, ...], "total_catalog": N}. Search by intent words, e.g. "test report", "mock patch", "update test case", "cloud replay branch", "record".