mcp-database-server
Supports installation on macOS systems via a specific configuration path.
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., "@mcp-database-servercreate a new document with title 'Project Plan' and status 'draft'"
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.
Model Context Protocol and Fireproof Demo: JSON Document Server
This is a simple example of how to use a Fireproof database in a Model Context Protocol server (used for plugging code and data into A.I. systems such as Claude Desktop).
This demo server implements a basic JSON document store with CRUD operations (Create, Read, Update, Delete) and the ability to query documents sorted by any field.
Installation
Install dependencies:
npm install
npm buildRunning the Server
To 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": {
"fireproof": {
"command": "/path/to/fireproof-mcp/build/index.js"
}
}
}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.
Available Tools
4 toolsdelete_json_docC
Delete a JSON document by ID
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ID of document to delete |
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. It states the tool deletes a document, implying a destructive mutation, but doesn't cover critical aspects like permissions needed, whether deletion is permanent or reversible, error handling, or rate limits. This is a significant gap for a destructive 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, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse quickly 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 the tool's complexity (destructive mutation) and lack of annotations or output schema, the description is incomplete. It fails to address behavioral traits like safety, permissions, or response format, leaving the agent under-informed for a critical 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?
Schema description coverage is 100%, with the 'id' parameter fully documented in the schema. The description adds no additional meaning beyond implying deletion targets a document by ID, which is already clear from the schema. Baseline 3 is appropriate as the schema handles parameter documentation adequately.
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 resource ('a JSON document by ID'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'load_json_doc' or 'save_json_doc' beyond the obvious verb difference, missing explicit sibling distinction.
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. The description lacks context about prerequisites (e.g., needing an existing document), exclusions, or comparisons to siblings like 'query_json_docs', leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
load_json_docC
Load a JSON document by ID
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ID of document to load |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the action without disclosing behavioral traits. It doesn't mention whether this is a read-only operation, potential errors (e.g., if ID doesn't exist), performance aspects, or authentication needs, leaving significant gaps in transparency.
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, front-loading the core action. It's appropriately sized for a simple tool, making it easy to parse quickly.
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's simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It lacks details on return values (e.g., document content or structure), error handling, or how it fits with siblings, leaving the agent with insufficient context for reliable use.
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 description adds minimal meaning beyond the input schema, which has 100% coverage and fully documents the 'id' parameter. It implies the ID is used for loading but doesn't provide additional context like ID format or source, meeting the baseline for high 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 'Load a JSON document by ID' clearly states the action (load) and resource (JSON document) with a specific mechanism (by ID). It distinguishes from siblings like delete_json_doc (deletion) and save_json_doc (saving), but could be more specific about what 'load' entails (e.g., retrieval vs. parsing).
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 query_json_docs (which might handle multiple documents or filtering). It lacks explicit context, prerequisites, or exclusions, leaving usage unclear beyond the basic action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_json_docsC
Query JSON documents sorted by a field
| Name | Required | Description | Default |
|---|---|---|---|
| sort_field | Yes | Field to sort results by |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions sorting behavior, but doesn't disclose critical traits like whether this is a read-only operation, if it requires authentication, what happens if no documents exist, or how results are returned (e.g., pagination, format). For a query tool with zero annotation coverage, this leaves significant gaps in understanding its 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 with no wasted words. It's front-loaded with the core action ('query JSON documents'), though it could be more structured by including key details like scope or output. Overall, it's concise but slightly under-specified.
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 querying documents and lack of annotations or output schema, the description is incomplete. It doesn't explain what the query returns (e.g., list of documents, counts), error conditions, or dependencies on other tools like 'save_json_doc'. For a tool with no structured behavioral data, this leaves the agent with insufficient 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?
Schema description coverage is 100%, with the parameter 'sort_field' fully documented in the schema. The description adds no additional meaning beyond what the schema provides, such as examples of sortable fields or sorting order. Baseline score of 3 is appropriate since the 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 states the action ('query') and resource ('JSON documents'), but is vague about scope and mechanism. It doesn't specify whether this queries all documents, filtered subsets, or specific collections, nor does it distinguish from siblings like 'load_json_doc' (which might retrieve a single document). The purpose is understandable but lacks specificity.
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. The description doesn't mention prerequisites, such as needing existing documents to query, or compare it to siblings like 'load_json_doc' for single-document retrieval. Usage context is implied from the name but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
save_json_docC
Save a JSON document
| Name | Required | Description | Default |
|---|---|---|---|
| doc | Yes | JSON document to save |
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. 'Save a JSON document' implies a write/mutation operation but fails to specify critical traits: whether it overwrites existing data, requires authentication, has rate limits, returns confirmation, or handles errors. This leaves significant gaps in understanding 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 with no wasted words, making it appropriately concise. However, it's overly brief to the point of under-specification, lacking necessary details for a mutation tool, which slightly reduces its effectiveness despite the clean structure.
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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'save' entails operationally, potential side effects, return values, or error conditions. Given the complexity implied by a write action and lack of structured data, more context is needed to adequately guide the agent.
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%, with the parameter 'doc' clearly documented as 'JSON document to save'. The description adds no additional meaning beyond this, such as format constraints or examples. Since the schema adequately covers the single parameter, the baseline score of 3 is appropriate, though no extra value is provided.
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 'Save a JSON document' restates the tool name 'save_json_doc' with minimal elaboration, making it tautological. It specifies the verb 'save' and resource 'JSON document' but lacks detail on what 'save' entails (e.g., storage location, persistence mechanism) and doesn't distinguish it from sibling tools like 'load_json_doc' or 'query_json_docs'.
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. The description doesn't mention prerequisites (e.g., needing an existing document to save over), exclusions, or comparisons to siblings like 'delete_json_doc' or 'load_json_doc', leaving the agent without context for selection.
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.
4 tool updates
v1.0.0- First observed
delete_json_doc - First observed
load_json_doc - First observed
query_json_docs - First observed
save_json_doc
TDQS
Each tool has a clearly distinct purpose with no overlap: load retrieves, save creates/updates, delete removes, and query searches documents. The descriptions make it easy for an agent to select the right tool for each operation without confusion.
All tool names follow a consistent verb_noun pattern (e.g., load_json_doc, save_json_doc) with snake_case throughout. The naming is predictable and readable, making it easy to understand each tool's function at a glance.
With 4 tools, this server is well-scoped for basic JSON document operations. Each tool earns its place by covering essential CRUD-like functions (load, save, delete, query), which is appropriate for a database server focused on JSON documents.
The tool set provides complete coverage for the domain of JSON document management: it includes create/update (save), read (load), delete, and query operations. There are no obvious gaps, and agents can perform full lifecycle tasks without dead ends.
Maintenance
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