CouchDB MCP Server
The CouchDB MCP Server is a TypeScript-based server that provides tools for managing CouchDB databases and documents, enabling AI assistants to interact with CouchDB through a simple interface.
Database Operations:
Create new databases using
createDatabaseList all available databases using
listDatabasesDelete existing databases using
deleteDatabase
Document Operations:
Create or update documents in a database using
createDocumentRetrieve documents from a database using
getDocument
Mango Query Capabilities (CouchDB 3.x+):
Create Mango indexes using
createMangoIndexDelete Mango indexes using
deleteMangoIndexList all Mango indexes in a database using
listMangoIndexesQuery documents using Mango query syntax with
findDocuments
Supports configuration through environment variables that can be stored in a .env file for CouchDB connection settings.
Provides specific configuration path information for Claude Desktop integration on macOS systems.
Serves as the runtime environment for the MCP server, with version 14 or higher required as a prerequisite.
The MCP server is implemented in TypeScript, providing type safety for CouchDB database interactions.
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., "@CouchDB MCP Servercreate a new database called 'customer_records'"
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.
couchdb-mcp-server
A Model Context Protocol server for interacting with CouchDB
This is a TypeScript-based MCP server that provides tools for managing CouchDB databases and documents. It enables AI assistants to interact with CouchDB through a simple interface.
Features
Tools
Base Tools (All CouchDB Versions)
createDatabase- Create a new CouchDB databaseTakes
dbNameas a required parameterCreates the database if it doesn't exist
listDatabases- List all CouchDB databasesReturns an array of database names
deleteDatabase- Delete a CouchDB databaseTakes
dbNameas a required parameterRemoves the specified database and all its documents
createDocument- Create a new document or update an existing document in a databaseRequired parameters:
dbName: Database namedocId: Document IDdata: Document data (JSON object)For updates, include
_revfield with the current document revision
Returns:
For new documents: document ID and new revision
For updates: document ID and updated revision
Automatically detects if operation is create or update based on presence of
_revfield
getDocument- Get a document from a databaseRequired parameters:
dbName: Database namedocId: Document ID
Returns the document content
Mango Query Tools (CouchDB 3.x+ Only)
createMangoIndex- Create a new Mango indexRequired parameters:
dbName: Database nameindexName: Name of the indexfields: Array of field names to index
Creates a new index for efficient querying
deleteMangoIndex- Delete a Mango indexRequired parameters:
dbName: Database namedesignDoc: Design document nameindexName: Name of the index
Removes an existing Mango index
listMangoIndexes- List all Mango indexes in a databaseRequired parameters:
dbName: Database name
Returns information about all indexes in the database
findDocuments- Query documents using Mango queryRequired parameters:
dbName: Database namequery: Mango query object
Performs a query using CouchDB's Mango query syntax
Related MCP server: MCP Docs RAG Server
Version Support
The server automatically detects the CouchDB version and enables features accordingly:
All versions: Basic database and document operations
CouchDB 3.x+: Mango query support (indexes and queries)
Configuration
The server requires a CouchDB connection URL and version. These can be provided through environment variables:
COUCHDB_URL=http://username:password@localhost:5984
COUCHDB_VERSION=1.7.2
You can create a `.env` file in the project root with this configuration. If not provided, it defaults to `http://localhost:5984`.
## Development
Install dependencies:
```bash
npm installBuild the server:
npm run buildFor development with auto-rebuild:
npm run watchInstallation
Installing via Smithery
To install couchdb-mcp-server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @robertoamoreno/couchdb-mcp-server --client claudeTo use with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"couchdb-mcp-server": {
"command": "/path/to/couchdb-mcp-server/build/index.js",
"env": {
"COUCHDB_URL": "http://username:password@localhost:5984"
}
}
}
}Prerequisites
Node.js 14 or higher
Running CouchDB instance
Proper CouchDB credentials if authentication is enabled
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspectorThe Inspector will provide a URL to access debugging tools in your browser.
Error Handling
The server includes robust error handling for common scenarios:
Invalid database names or document IDs
Database already exists/doesn't exist
Connection issues
Authentication failures
Invalid document data
All errors are properly formatted and returned through the MCP protocol with appropriate error codes and messages.
Available Tools
5 toolscreateDatabaseC
Create a new CouchDB database
| Name | Required | Description | Default |
|---|---|---|---|
| dbName | Yes | Database name |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates a database but lacks critical details: it doesn't specify if this requires admin privileges, what happens if the database already exists (e.g., error or overwrite), or any rate limits or side effects. This leaves significant gaps for an agent to understand the tool's behavior.
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, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly, though it could benefit from more detail given the lack of annotations.
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 complexity of a database creation tool with no annotations and no output schema, the description is insufficient. It doesn't cover behavioral aspects like permissions, error handling, or what the tool returns upon success. For a mutation tool with zero annotation coverage, more completeness is needed to guide an agent effectively.
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 100% description coverage, with 'dbName' documented as 'Database name'. The description adds no additional meaning beyond this, such as naming conventions, length restrictions, or character constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but the description doesn't compensate with extra context.
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 ('Create') and resource ('a new CouchDB database'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'createDocument' or 'listDatabases', which would require more specificity about what distinguishes database creation from document creation.
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 versus alternatives like 'createDocument' or 'deleteDatabase'. There's no mention of prerequisites, such as needing admin permissions or checking if a database already exists, nor any explicit exclusions or recommended contexts for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
createDocumentC
Create a new document or update an existing document in a database
| Name | Required | Description | Default |
|---|---|---|---|
| dbName | Yes | Database name | |
| docId | Yes | Document ID | |
| data | Yes | Document data |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions the tool can both create and update documents, it doesn't specify whether updates are partial or full replacements, what permissions are required, whether operations are idempotent, or what happens on conflicts. For a mutation tool with zero annotation coverage, this leaves significant behavioral gaps.
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, efficient sentence that clearly states the tool's dual functionality. It's appropriately sized for the tool's purpose without unnecessary elaboration, though it could potentially be more front-loaded with critical behavioral information given the lack of annotations.
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 document creation/update tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens when creating versus updating, what the response looks like, error conditions, or important behavioral constraints. Given the mutation nature and complexity of the operation, more contextual information is needed.
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 100% description coverage, so all three parameters (dbName, docId, data) are documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema, such as format requirements for docId or constraints on data structure. This meets the baseline expectation when schema coverage is complete.
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 purpose with specific verbs ('create' and 'update') and resource ('document in a database'), making it easy to understand what the tool does. However, it doesn't explicitly distinguish this from sibling tools like 'createDatabase' or 'getDocument', which would require more specific differentiation.
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 versus alternatives like 'createDatabase' for creating databases or 'getDocument' for retrieving documents. There's no mention of prerequisites, error conditions, or typical use cases, leaving the agent with insufficient context for appropriate tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
deleteDatabaseC
Delete a CouchDB database
| Name | Required | Description | Default |
|---|---|---|---|
| dbName | Yes | Database name to delete |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'Delete' which implies a destructive mutation, but doesn't disclose critical behavioral traits: whether deletion is permanent, if it requires specific permissions, what happens to contained documents, or error conditions. This is a significant gap for a destructive tool.
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, efficient sentence with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration.
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 this is a destructive mutation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what happens after deletion (success/failure responses), doesn't warn about irreversible data loss, and doesn't provide context about the CouchDB environment. For a tool that permanently removes resources, this lacks critical completeness.
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 100% (the single parameter 'dbName' is fully described in the schema as 'Database name to delete'). The description doesn't add any parameter meaning beyond what the schema provides, so it meets the baseline of 3 when schema does the heavy lifting.
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 target resource ('a CouchDB database'), providing specific verb+resource pairing. It doesn't explicitly distinguish from sibling tools like 'createDatabase' or 'listDatabases', but the verb 'Delete' inherently differentiates it from creation and listing operations.
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 about when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., database must exist), consequences (e.g., irreversible data loss), or relationships to sibling tools like 'createDatabase' for recreation or 'listDatabases' for verification.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
getDocumentC
Get a document from a database
| Name | Required | Description | Default |
|---|---|---|---|
| dbName | Yes | Database name | |
| docId | Yes | Document ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves a document but lacks details on permissions required, error handling (e.g., if the document doesn't exist), response format, or any side effects. This is a significant gap for a read operation in a database context, where such information is crucial for safe usage.
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, efficient sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded with the core action and resource, making it easy to parse. Every part of the sentence earns its place by conveying essential information, achieving optimal 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?
Given the complexity of database operations and the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like error cases, return values, or security requirements, which are critical for an agent to use the tool effectively. The description alone is insufficient for safe and informed tool invocation in this context.
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 100% description coverage, with clear documentation for both parameters ('dbName' and 'docId'). The description adds no additional meaning beyond what the schema provides, such as examples or constraints. According to the rules, when schema coverage is high (>80%), the baseline score is 3, which applies here as the description doesn't compensate with extra param details.
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 resource ('a document from a database'), making the purpose immediately understandable. It distinguishes from siblings like 'createDocument' and 'deleteDatabase' by specifying retrieval rather than creation or deletion. However, it doesn't explicitly differentiate from 'listDatabases' in terms of scope (single document vs. listing databases), which prevents a perfect score.
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 versus alternatives. It doesn't mention prerequisites (e.g., needing an existing database and document), exclusions (e.g., not for creating or deleting), or comparisons to sibling tools like 'listDatabases' for broader queries. This leaves the agent with minimal context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
listDatabasesB
List all CouchDB databases
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe how it behaves - no information about pagination, rate limits, authentication requirements, error conditions, or return format. 'List all' implies completeness but doesn't guarantee it.
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, efficient sentence that states exactly what the tool does with zero wasted words. It's appropriately sized for a simple list operation and front-loads the core functionality.
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 read operation with no annotations and no output schema, the description is insufficient. It doesn't explain what the output looks like (array of database names? objects with metadata?), potential limitations, or error handling. The agent would need to guess about the return format and behavior.
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 schema description coverage is 100% (though empty). The description appropriately doesn't discuss parameters since none exist, earning a baseline score of 4 for tools with no parameters.
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') and target resource ('all CouchDB databases'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'getDocument' or 'createDatabase' beyond the obvious scope difference, which prevents a perfect score.
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 about when to use this tool versus alternatives. While the purpose is clear, there's no mention of prerequisites, timing considerations, or comparison to sibling tools like 'getDocument' for retrieving specific database information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Each tool has a distinct purpose targeting specific resources and actions: createDatabase, deleteDatabase, and listDatabases handle database-level operations, while createDocument and getDocument handle document-level operations. There is no overlap or ambiguity between tools.
All tool names follow a consistent verb_noun pattern (e.g., createDatabase, getDocument) using camelCase throughout. The naming is predictable and uniform across all five tools.
With 5 tools, this server is well-scoped for basic CouchDB operations, covering database and document management without being overly sparse or bloated. Each tool serves a clear and necessary function.
The toolset covers core CRUD operations for databases (create, delete, list) and documents (create, get), but lacks document deletion and update tools, which are common in database workflows. This minor gap might require workarounds but does not severely hinder functionality.
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