skysql-mcp
OfficialThis server is an MCP server for managing SkySQL/MariaDB Cloud database instances and interacting with AI-powered database agents.
Launch new serverless MariaDB database instances
Delete existing database instances
List all available SkySQL database services
Retrieve credentials for a database instance
Update the IP allowlist for a database instance
Execute SQL queries directly on a SkySQL instance
List available SkySQL DB agents and their capabilities
Ask questions to a specific AI database agent
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@skysql-mcpshow me my database instances"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
SkySQL MCP Server
This package contains everything needed to set up the SkySQL/MariaDB Cloud MCP (Model Context Protocol) server, which provides a powerful interface for managing SkySQL MariaDB database instances and interacting with AI Agents.
Features
Launch and manage serverless MariaDB database instances
Interact with AI-powered database agents
Execute SQL queries directly on SkySQL (MySQL/MariaDB) instances
Manage database credentials and IP allowlists
List and monitor database services
Related MCP server: MySQL MCP Server Pro
Installation
Prerequisites
Python 3.10 or higher
A SkySQL/MariaDB Cloud API key
Option 1: Run locally
Installation steps
Clone the repository:
git clone git@github.com:skysqlinc/skysql-mcp.git cd skysql-mcpRun the installation script:
chmod +x install.sh ./install.shCreate a
.envfile in the root directory of the cloned git repository with your SkySQL API key. Obtain API key by signing up for free on SkySQL.SKYSQL_API_KEY=<your_skysql_api_key_here>Start the MCP server (HTTP mode):
chmod +x launch.sh ./launch.shThe server will start on
http://localhost:8000/mcpby default.Configure your IDE:
Cursor
Add the following to your Cursor MCP config (~/.cursor/mcp.json or .cursor/mcp.json in your project):
{
"mcpServers": {
"skysql-mcp-server": {
"url": "http://localhost:8000/mcp",
"headers": {
"X-API-Key": "<your-skysql-api-key>"
}
}
}
}The
X-API-Keyheader is sent with each request, allowing per-user API keys when the server is hosted remotely.
Windsurf
Add the following to your Windsurf MCP config (~/.codeium/windsurf/mcp_config.json):
{
"mcpServers": {
"skysql-mcp-server": {
"serverUrl": "http://localhost:8000/mcp"
}
}
}Note: Windsurf uses
serverUrl(noturl) and cannot send request headers. Start the server in single-tenant mode so it falls back to the API key in your environment:SKYSQL_SINGLE_TENANT=true ./launch.shWith
SKYSQL_API_KEYset in.env(step 3). WithoutSKYSQL_SINGLE_TENANT, the server requires every HTTP caller to supply its ownX-API-Keyheader and will reject requests that don't — deliberately, so a shared deployment can never serve requests using the operator's key.
Claude
Add the server as a custom connector (Settings > Connectors > Add custom connector), then supply your API key under Request headers:
Field | Value |
URL | your deployed server URL, ending in |
Header name |
|
Header value | your SkySQL API key, with no prefix |
Required | yes |
Generate the key at app.skysql.com/user-profile/api-keys. Enter it exactly as-is — Claude sends the value verbatim and does not add a scheme or prefix.
Claude requires a publicly reachable HTTPS URL, so
http://localhost:8000/mcpwill not work here; deploy the server first. Request header authentication is currently in beta and may need to be enabled for your organization.
(Optional) Test the server interactively with MCP CLI:
npx @wong2/mcp-cli uv run python src/mcp-server/server.py
Available Tools
8 toolsask_agentB
Ask a question to a specific DB agent
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes | ||
| question | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits, but it only states the action without disclosing side effects, return behavior, or prerequisites. The existence of an output schema mitigates the need to describe return format, but the description still doesn't clarify if this is a read-only operation or if there are any mutating effects, leaving a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundant words. It is appropriately concise for a simple two-parameter tool, and the essential purpose is stated up front.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having only two parameters and an output schema, the description leaves out critical usage context: it does not explain when to use this tool instead of execute_sql, how to determine the correct agent_id, or what types of questions are supported. The tool is part of a DB-related set, and such context is necessary for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero property descriptions, so the description must compensate. It clarifies that agent_id refers to a specific agent, but offers no details about the question parameter (e.g., language, format, allowed topics) or how to obtain valid agent_ids. This minimal addition is insufficient given the complete lack of schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Ask a question to a specific DB agent' clearly states the action (ask) and target (a specific DB agent), distinguishing it from sibling tools like list_agents, execute_sql, and delete_db. It also implies the need for an identifier, which aligns with the required agent_id parameter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., when to use execute_sql instead of asking an agent, or how to obtain agent_id via list_agents). The description offers no contextual direction for selection or preconditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_dbC
Delete a DB instance from SkySQL
| Name | Required | Description | Default |
|---|---|---|---|
| service_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. For a destructive delete operation, it fails to disclose irreversibility, potential cascade effects, or any other side effects, providing no behavioral information beyond the action itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words, directly stating the action and scope. It is front-loaded and free of fluff, earning a high score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite an output schema, the description is far from complete. It omits any mention of return values, the effect on associated resources, or how service_id relates to sibling tools like list_services. This is particularly deficient for a destructive operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema includes a required service_id with no description (0% coverage). The description does not explain what this parameter is, how to find it, or its format, so it fails to compensate for the missing schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and the target ('DB instance from SkySQL'), using a specific verb and resource. This unambiguously distinguishes it from sibling tools like launch_serverless_db or list_services.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool, prerequisites, or exclusions. It doesn't mention how to obtain the service_id (e.g., via list_services) or warn about destructive consequences.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
execute_sqlC
Execute SQL query on a SkySQL database instance and return the results
| Name | Required | Description | Default |
|---|---|---|---|
| sql_query | Yes | ||
| service_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source of behavioral disclosure. It only states that it executes a query and returns results, but does not mention potential side effects, permissions required, rate limits, or whether the query can modify data. This leaves the agent in the dark about risks associated with arbitrary SQL execution.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that conveys the core purpose without any redundant words. It is front-loaded and efficiently structured, every word earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists and the tool has only two parameters, the description is incomplete for practical use. It lacks usage guidelines, parameter clarification, and behavioral nuance (e.g., whether the query is read/write). This is insufficient for an agent to select and invoke the tool reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides only parameter names (service_id and sql_query) with no descriptions. Schema description coverage is 0%, and the description does not explain what these parameters mean or how to use them. The agent cannot infer the expected format or purpose of each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Execute SQL query on a SkySQL database instance and return the results.' It uses a specific verb ('Execute') and identifies the resource (SQL query on a SkySQL instance), which distinguishes it from sibling tools that manage services or agents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusions. For instance, it doesn't clarify whether this is for read-only queries or DDL/DML, or when to prefer ask_agent or list_services.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_db_credentialsB
Get the credentials for a SkySQL database instance
| Name | Required | Description | Default |
|---|---|---|---|
| service_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavior. It only states that it retrieves credentials, without disclosing what is returned, whether it's a secure operation, or any side effects. The absence of detail makes it difficult for an agent to know what to expect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that is front-loaded and concise. However, it is under-specified, which limits its value despite its brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter) and has an output schema, which mitigates the need for return-value documentation. However, the description lacks contextual details such as when to use this tool, how it relates to launching or listing services, and any prerequisites, making it only minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one required parameter 'service_id' with no description. The tool description mentions 'database instance' but does not explicitly map 'service_id' to that concept or provide any additional meaning. With 0% schema coverage, the description fails to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('credentials for a SkySQL database instance'), distinguishing it from sibling tools that manage services or execute SQL.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool, prerequisites, or alternatives. It lacks any context about how to obtain the service_id or whether this tool should be used in conjunction with other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
launch_serverless_dbC
Launch a new Serverless DB instance in SkySQL
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| region | No | eastus | |
| provider | No | azure |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it only states the action. It does not disclose whether the launch is synchronous, how long it takes, potential side effects (e.g., costs, resource limits), or what happens on success/failure. This is minimal behavior disclosure for a create operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the action. It has no fluff or repetition, which earns a high score for conciseness, though it lacks depth that would be useful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema and 3 parameters, the description provides no operational context. It doesn't cover the parameters, the expected output semantics beyond 'launch', or any constraints. This is inadequate for a tool that creates a cloud resource.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate by explaining any parameters. The fields name, region, and provider are left entirely undefined, leaving the agent to guess their meaning, defaults, and allowed values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Launch a new Serverless DB instance' with a specific resource and scope ('in SkySQL'). It differentiates from siblings like delete_db and list_services by the verb 'launch' and the serverless DB context, though it does not explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. It doesn't mention prerequisites, typical scenarios, or exclusions. The description simply states what it does without any contextual usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_agentsA
List all available SkySQL DB agents with their capabilities
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It indicates a read-only listing operation ('List all available...') but does not disclose potential side effects, authentication requirements, or limitations (e.g., whether only agents accessible to the current user are returned). For a simple list tool, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is clear and free of filler. It efficiently communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists and the tool has no parameters, the description is largely complete. It might benefit from a note about the structure of the returned list, but the output schema likely covers that. The description focuses on the 'what' without overspecifying.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline is 4. The description adds no parameter-specific details, but none are needed. The phrase 'all available' clarifies scope.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List'), the resource ('all available SkySQL DB agents'), and the additional detail ('with their capabilities'). This distinguishes it from sibling tools like list_services, which lists services, and ask_agent, which likely interacts with an agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as list_services or ask_agent. The description implies a simple listing operation but does not mention exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_servicesA
List all available SkySQL database services
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. The verb 'List' implies a read-only, non-destructive operation, and 'all available' defines scope. However, it doesn't mention authentication, rate limits, pagination, or other behavioral details, but for a simple list operation this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that clearly states the action and resource. It is front-loaded and contains no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is a simple list operation with no parameters and an output schema exists, the description is fully sufficient. It clearly identifies the resource and scope, making it complete for a situation with low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema confirms an empty object. The description adds no parameter details, but with no parameters to describe, a baseline of 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and identifies the resource as 'SkySQL database services', making it clear what the tool does. It also distinguishes from siblings like list_agents by specifying the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: when you need to see all available database services. It doesn't explicitly mention alternatives or exclusions, but the context is unambiguous given the simple, read-only nature and resource specificity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_ip_allowlistC
Update the IP allowlist for a SkySQL database instance with the current IP
| Name | Required | Description | Default |
|---|---|---|---|
| service_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for disclosing behavior. It only states the update action without revealing whether the allowlist is overwritten or appended, whether permissions are required, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, focused sentence with no filler words. It immediately conveys the core action and target.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter tool with an output schema, the description is minimal. It lacks essential context about how to determine service_id, what the output represents, and potential error conditions, making it incomplete for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter service_id is not explained in the description; the description does not connect it to the database instance. With 0% schema coverage, this leaves the agent without parameter-level guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action (update), the resource (IP allowlist), and the target (SkySQL database instance). 'With the current IP' adds specificity, distinguishing it from other database management tools like delete_db.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool, prerequisites, or alternatives. The description does not mention related tools like list_services for finding service_id, nor does it explain when an update would be appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
8 tool updates
v0.1.0- First observed
ask_agent - First observed
delete_db - First observed
execute_sql - First observed
get_db_credentials - First observed
launch_serverless_db - First observed
list_agents - First observed
list_services - First observed
update_ip_allowlist
TDQS
Tools are mostly distinct, covering agent interactions and database lifecycle management. The only slight overlap is between list_agents and list_services, but the entity types (agents vs services) are clearly different, reducing selection risk.
All tool names follow a consistent verb_noun pattern (list, launch, delete, ask, get, update, execute), with no mixed conventions or unclear verbs. The naming is predictable and readable.
With 8 tools, the server is well-scoped for its purpose, balancing database operations with agent interaction without redundancy or unnecessary bloat.
Core database lifecycle is covered (launch, delete, list, credentials, SQL execution), plus agent interaction. Minor gaps exist, such as lack of explicit service status checks or credential rotation, but these are not critical for the main workflows.
Maintenance
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