QVeris MCP Server Documentation

What it is

@qverisai/mcp is the official QVeris MCP server for MCP-compatible clients such as Cursor, Claude Desktop, and other coding agents.

It gives agents access to QVeris through a small set of MCP tools:

discover — Find capabilities by natural language
inspect — Get detailed tool info (params, success rate, examples)
call — Execute a tool with parameters
usage_history — Context-safe usage audit summary/search/export
credits_ledger — Context-safe final credit ledger summary/search/export

In other words, the MCP server is the agent-facing transport for the same core QVeris protocol described elsewhere in this repository.

MCP vs REST API

Use the MCP server when:

You are integrating QVeris into Cursor, Claude Desktop, OpenCode, or another MCP client
You want the agent to call QVeris tools directly in chat
You want the client to manage tool invocation automatically

Use the REST API when:

You are writing application code or backend services
You need direct HTTP control over requests and responses
You are building SDK wrappers or production integrations

Both surfaces map to the same QVeris protocol:

Protocol action	MCP tool	REST API
Discover	`discover`	`POST /search`
Inspect	`inspect`	`POST /tools/by-ids`
Call	`call`	`POST /tools/execute`
Usage audit	`usage_history`	`GET /auth/usage/history/v2`
Credits ledger	`credits_ledger`	`GET /auth/credits/ledger`

Note: The old tool names (search_tools, get_tools_by_ids, execute_tool) are still supported as deprecated aliases.

Requirements

Node.js 18+
A valid QVERIS_API_KEY
An MCP-compatible client

Quick Start

Install via `npx`

npx -y @qverisai/mcp

The MCP server reads configuration from environment variables:

QVERIS_API_KEY=your-api-key          # Required
QVERIS_BASE_URL=https://qveris.ai/api/v1  # Optional: override API base URL

Configure with QVeris CLI

Use the CLI to generate client config without hand-editing JSON. By default it prints a safe config with YOUR_QVERIS_API_KEY placeholders; placeholder output intentionally fails API key validation until you replace it or use --include-key.

# Print safe Cursor config
qveris mcp configure --target cursor

# Write a working config using the API key from qveris login or QVERIS_API_KEY
qveris mcp configure --target cursor --write --include-key
qveris mcp configure --target claude-desktop --write --include-key
qveris mcp configure --target opencode --write --include-key
qveris mcp configure --target openclaw --write --include-key

# Claude Code uses a shell command instead of a JSON config file
qveris mcp configure --target claude-code

Validate a config before restarting the client:

qveris mcp validate --target cursor

For stdio clients, add --probe to start the configured MCP server and confirm that discover, inspect, and call are visible via tools/list:

qveris mcp validate --target cursor --probe

Claude Desktop example

{
  "mcpServers": {
    "qveris": {
      "command": "npx",
      "args": ["-y", "@qverisai/mcp"],
      "env": {
        "QVERIS_API_KEY": "your-api-key-here"
      }
    }
  }
}

Cursor example

{
  "mcpServers": {
    "qveris": {
      "command": "npx",
      "args": ["-y", "@qverisai/mcp"],
      "env": {
        "QVERIS_API_KEY": "your-api-key-here"
      }
    }
  }
}

For environment-specific setup guides, see:

Hosted MCP

QVeris provides a remote Streamable HTTP MCP service. It requires no local package or background process. If the endpoint is not yet available, continue using the local stdio package shown above while the hosted service rollout completes.

https://mcp.qveris.ai/mcp

Add the endpoint to a remote-MCP-compatible client and send your QVeris API key on every request:

{
  "mcpServers": {
    "qveris": {
      "type": "http",
      "url": "https://mcp.qveris.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_QVERIS_API_KEY"
      }
    }
  }
}

Claude Code can add it from the command line:

claude mcp add --transport http qveris https://mcp.qveris.ai/mcp --scope user --header "Authorization: Bearer YOUR_QVERIS_API_KEY"

Setup flow:

Create a key on Dashboard / API Keys.
Add the endpoint and Bearer header to your client. Store the key in a secret or environment variable when supported; never commit it.
Reconnect the client and confirm discover, inspect, and call are visible.

The server validates the key when a session starts and binds that session to the credential. A 401 means the key is missing or invalid; a 503 means validation is temporarily unavailable. Start a new MCP session after changing the key. See the Hosted MCP page for a copy-ready setup.

The local stdio package remains available for clients that do not support remote Streamable HTTP MCP.

Available MCP Tools

1. `discover`

Use this tool to find capabilities with natural language.

This is the Discover action and is free.

Parameter	Type	Required	Description
`query`	string	Yes	Natural-language description of the capability you need
`limit`	number	No	Max results to return (`1-100`, default `20`)
`session_id`	string	No	Session identifier for tracking

Example:

{
  "query": "weather forecast API",
  "limit": 10
}

Typical response fields:

search_id
total
results[]
results[].tool_id
results[].params
results[].examples
results[].stats

2. `inspect`

Use this tool to inspect one or more known tool_ids before reuse or execution.

This is the Inspect action.

Parameter	Type	Required	Description
`tool_ids`	array	Yes	Array of tool IDs to retrieve
`search_id`	string	No	Search ID from the discovery that returned the tool(s)
`session_id`	string	No	Session identifier for tracking

Example:

{
  "tool_ids": ["openweathermap.weather.execute.v1"],
  "search_id": "YOUR_SEARCH_ID"
}

Use inspect when:

Multiple candidates look similar
You want to re-check parameters before calling
You want to inspect success rate or latency
You are reusing a tool found in an earlier turn

The response schema matches /search for the requested tools, including parameters, examples, and stats.

3. `call`

Use this tool to call a discovered QVeris capability.

The call response may include compact pre-settlement billing. Final charge status should be checked with usage_history or credits_ledger.

Parameter	Type	Required	Description
`tool_id`	string	Yes	Tool ID from discovery results
`search_id`	string	Yes	Search ID from the discovery that found this tool
`params_to_tool`	object	Yes	Dictionary of parameters to pass to the tool
`session_id`	string	No	Session identifier for tracking
`max_response_size`	number	No	Max response size in bytes (default `20480`)

Example:

{
  "tool_id": "openweathermap.weather.execute.v1",
  "search_id": "YOUR_SEARCH_ID",
  "params_to_tool": {"city": "London", "units": "metric"}
}

Typical successful response fields:

execution_id
tool_id
success
result.data
elapsed_time_ms or execution_time
billing / pre_settlement_bill when available

4. `usage_history`

Use this tool when the user asks whether a call succeeded, failed, or charged credits. It defaults to summary mode and does not dump full history into context.

Useful inputs:

mode: summary, search, or export_file
execution_id or search_id for precise lookup
charge_outcome for charged, included, failed_not_charged, or failed_charged_review
min_credits / max_credits for amount ranges
start_date / end_date for time windows

Summary mode requests service-side summary=true aggregates when available and falls back to bounded client-side aggregation for older deployments.

Examples:

{ "mode": "summary", "bucket": "hour" }

{ "mode": "search", "execution_id": "EXECUTION_ID" }

5. `credits_ledger`

Use this tool when the user asks why their balance changed. It defaults to summary mode.

Useful inputs:

mode: summary, search, or export_file
direction: consume, grant, or any
entry_type
min_credits / max_credits
start_date / end_date

Summary mode requests service-side summary=true aggregates when available and falls back to bounded client-side aggregation for older deployments.

Examples:

{ "mode": "summary", "bucket": "day" }

{ "mode": "search", "direction": "consume", "min_credits": 50 }

Large result sets should use mode: "export_file". The MCP server writes JSONL under .qveris/exports/ and returns the file path instead of emitting every row.

For very large call outputs, QVeris may return:

truncated_content
full_content_file_url
message

Recommended Usage Pattern

For most agent tasks, use this flow:

discover to find relevant capabilities
inspect to review the best candidate(s) when needed
call to execute the selected capability

In practice:

If the task is simple and the best candidate is obvious, you may go directly from Discover to Call
If the task is higher risk or parameters are unclear, insert Inspect before Call
If you already know a good tool_id from a previous turn, re-inspect it before reuse

Session Management

Providing a consistent session_id across a single user session helps with:

User-session continuity
Better tool selection over time
More coherent analytics and tracing

If session_id is omitted, the MCP server may generate one for the lifetime of the server process.

Troubleshooting

MCP server does not appear in the client

Confirm Node.js is installed: node --version
Confirm the client MCP config is valid JSON
Confirm QVERIS_API_KEY is set correctly
Restart the MCP client after configuration changes

Tools are visible but calls fail

Verify the API key is valid
Verify the selected tool_id came from a prior discovery
Re-run inspect to inspect the tool before calling
Check that params_to_tool is a valid object

Windows-specific issues

If direct npx execution fails in some clients, wrap with cmd /c:

{
  "command": "cmd",
  "args": ["/c", "npx", "-y", "@qverisai/mcp"]
}

Related Docs

QVeris MCP Server Documentation

What it is

@qverisai/mcp is the official QVeris MCP server for MCP-compatible clients such as Cursor, Claude Desktop, and other coding agents.

It gives agents access to QVeris through a small set of MCP tools:

discover — Find capabilities by natural language
inspect — Get detailed tool info (params, success rate, examples)
call — Execute a tool with parameters
usage_history — Context-safe usage audit summary/search/export
credits_ledger — Context-safe final credit ledger summary/search/export

In other words, the MCP server is the agent-facing transport for the same core QVeris protocol described elsewhere in this repository.

MCP vs REST API

Use the MCP server when:

You are integrating QVeris into Cursor, Claude Desktop, OpenCode, or another MCP client
You want the agent to call QVeris tools directly in chat
You want the client to manage tool invocation automatically

Use the REST API when:

You are writing application code or backend services
You need direct HTTP control over requests and responses
You are building SDK wrappers or production integrations

Both surfaces map to the same QVeris protocol:

Protocol action	MCP tool	REST API
Discover	`discover`	`POST /search`
Inspect	`inspect`	`POST /tools/by-ids`
Call	`call`	`POST /tools/execute`
Usage audit	`usage_history`	`GET /auth/usage/history/v2`
Credits ledger	`credits_ledger`	`GET /auth/credits/ledger`

Note: The old tool names (search_tools, get_tools_by_ids, execute_tool) are still supported as deprecated aliases.

Requirements

Node.js 18+
A valid QVERIS_API_KEY
An MCP-compatible client

Quick Start

Install via `npx`

npx -y @qverisai/mcp

The MCP server reads configuration from environment variables:

QVERIS_API_KEY=your-api-key          # Required
QVERIS_BASE_URL=https://qveris.ai/api/v1  # Optional: override API base URL

Configure with QVeris CLI

# Print safe Cursor config
qveris mcp configure --target cursor

# Write a working config using the API key from qveris login or QVERIS_API_KEY
qveris mcp configure --target cursor --write --include-key
qveris mcp configure --target claude-desktop --write --include-key
qveris mcp configure --target opencode --write --include-key
qveris mcp configure --target openclaw --write --include-key

# Claude Code uses a shell command instead of a JSON config file
qveris mcp configure --target claude-code

Validate a config before restarting the client:

qveris mcp validate --target cursor

For stdio clients, add --probe to start the configured MCP server and confirm that discover, inspect, and call are visible via tools/list:

qveris mcp validate --target cursor --probe

Claude Desktop example

{
  "mcpServers": {
    "qveris": {
      "command": "npx",
      "args": ["-y", "@qverisai/mcp"],
      "env": {
        "QVERIS_API_KEY": "your-api-key-here"
      }
    }
  }
}

Cursor example

{
  "mcpServers": {
    "qveris": {
      "command": "npx",
      "args": ["-y", "@qverisai/mcp"],
      "env": {
        "QVERIS_API_KEY": "your-api-key-here"
      }
    }
  }
}

For environment-specific setup guides, see:

Hosted MCP

https://mcp.qveris.ai/mcp

Add the endpoint to a remote-MCP-compatible client and send your QVeris API key on every request:

{
  "mcpServers": {
    "qveris": {
      "type": "http",
      "url": "https://mcp.qveris.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_QVERIS_API_KEY"
      }
    }
  }
}

Claude Code can add it from the command line:

claude mcp add --transport http qveris https://mcp.qveris.ai/mcp --scope user --header "Authorization: Bearer YOUR_QVERIS_API_KEY"

Setup flow:

Create a key on Dashboard / API Keys.
Add the endpoint and Bearer header to your client. Store the key in a secret or environment variable when supported; never commit it.
Reconnect the client and confirm discover, inspect, and call are visible.

The local stdio package remains available for clients that do not support remote Streamable HTTP MCP.

Available MCP Tools

1. `discover`

Use this tool to find capabilities with natural language.

This is the Discover action and is free.

Parameter	Type	Required	Description
`query`	string	Yes	Natural-language description of the capability you need
`limit`	number	No	Max results to return (`1-100`, default `20`)
`session_id`	string	No	Session identifier for tracking

Example:

{
  "query": "weather forecast API",
  "limit": 10
}

Typical response fields:

search_id
total
results[]
results[].tool_id
results[].params
results[].examples
results[].stats

2. `inspect`

Use this tool to inspect one or more known tool_ids before reuse or execution.

This is the Inspect action.

Parameter	Type	Required	Description
`tool_ids`	array	Yes	Array of tool IDs to retrieve
`search_id`	string	No	Search ID from the discovery that returned the tool(s)
`session_id`	string	No	Session identifier for tracking

Example:

{
  "tool_ids": ["openweathermap.weather.execute.v1"],
  "search_id": "YOUR_SEARCH_ID"
}

Use inspect when:

Multiple candidates look similar
You want to re-check parameters before calling
You want to inspect success rate or latency
You are reusing a tool found in an earlier turn

The response schema matches /search for the requested tools, including parameters, examples, and stats.

3. `call`

Use this tool to call a discovered QVeris capability.

The call response may include compact pre-settlement billing. Final charge status should be checked with usage_history or credits_ledger.

Parameter	Type	Required	Description
`tool_id`	string	Yes	Tool ID from discovery results
`search_id`	string	Yes	Search ID from the discovery that found this tool
`params_to_tool`	object	Yes	Dictionary of parameters to pass to the tool
`session_id`	string	No	Session identifier for tracking
`max_response_size`	number	No	Max response size in bytes (default `20480`)

Example:

{
  "tool_id": "openweathermap.weather.execute.v1",
  "search_id": "YOUR_SEARCH_ID",
  "params_to_tool": {"city": "London", "units": "metric"}
}

Typical successful response fields:

execution_id
tool_id
success
result.data
elapsed_time_ms or execution_time
billing / pre_settlement_bill when available

4. `usage_history`

Use this tool when the user asks whether a call succeeded, failed, or charged credits. It defaults to summary mode and does not dump full history into context.

Useful inputs:

mode: summary, search, or export_file
execution_id or search_id for precise lookup
charge_outcome for charged, included, failed_not_charged, or failed_charged_review
min_credits / max_credits for amount ranges
start_date / end_date for time windows

Summary mode requests service-side summary=true aggregates when available and falls back to bounded client-side aggregation for older deployments.

Examples:

{ "mode": "summary", "bucket": "hour" }

{ "mode": "search", "execution_id": "EXECUTION_ID" }

5. `credits_ledger`

Use this tool when the user asks why their balance changed. It defaults to summary mode.

Useful inputs:

mode: summary, search, or export_file
direction: consume, grant, or any
entry_type
min_credits / max_credits
start_date / end_date

Summary mode requests service-side summary=true aggregates when available and falls back to bounded client-side aggregation for older deployments.

Examples:

{ "mode": "summary", "bucket": "day" }

{ "mode": "search", "direction": "consume", "min_credits": 50 }

Large result sets should use mode: "export_file". The MCP server writes JSONL under .qveris/exports/ and returns the file path instead of emitting every row.

For very large call outputs, QVeris may return:

truncated_content
full_content_file_url
message

Recommended Usage Pattern

For most agent tasks, use this flow:

discover to find relevant capabilities
inspect to review the best candidate(s) when needed
call to execute the selected capability

In practice:

If the task is simple and the best candidate is obvious, you may go directly from Discover to Call
If the task is higher risk or parameters are unclear, insert Inspect before Call
If you already know a good tool_id from a previous turn, re-inspect it before reuse

Session Management

Providing a consistent session_id across a single user session helps with:

User-session continuity
Better tool selection over time
More coherent analytics and tracing

If session_id is omitted, the MCP server may generate one for the lifetime of the server process.

Troubleshooting

MCP server does not appear in the client

Confirm Node.js is installed: node --version
Confirm the client MCP config is valid JSON
Confirm QVERIS_API_KEY is set correctly
Restart the MCP client after configuration changes

Tools are visible but calls fail

Verify the API key is valid
Verify the selected tool_id came from a prior discovery
Re-run inspect to inspect the tool before calling
Check that params_to_tool is a valid object

Windows-specific issues

If direct npx execution fails in some clients, wrap with cmd /c:

{
  "command": "cmd",
  "args": ["/c", "npx", "-y", "@qverisai/mcp"]
}

QVeris MCP Server Documentation

What it is

MCP vs REST API

Requirements

Quick Start

Install via npx

Configure with QVeris CLI

Claude Desktop example

Cursor example

Hosted MCP

Available MCP Tools

1. discover

2. inspect

3. call

4. usage_history

5. credits_ledger

Recommended Usage Pattern

Session Management

Troubleshooting

MCP server does not appear in the client

Tools are visible but calls fail

Windows-specific issues

Related Docs

QVeris MCP Server Documentation

What it is

MCP vs REST API

Requirements

Quick Start

Install via npx

Configure with QVeris CLI

Claude Desktop example

Cursor example

Hosted MCP

Available MCP Tools

1. discover

2. inspect

3. call

4. usage_history

5. credits_ledger

Recommended Usage Pattern

Session Management

Troubleshooting

MCP server does not appear in the client

Tools are visible but calls fail

Windows-specific issues

Related Docs

Install via `npx`

1. `discover`

2. `inspect`

3. `call`

4. `usage_history`

5. `credits_ledger`

Install via `npx`

1. `discover`

2. `inspect`

3. `call`

4. `usage_history`

5. `credits_ledger`