How do I use zbmath-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@zbmath-mcp search for recent papers on quantum topology" 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.

zbmath-mcp

by iwaokimura

Overview Schema Related Servers Score Discussions

Python

Remote

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., "@zbmath-mcp search for recent papers on quantum topology"

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.

zbmath-mcp

MCP server for zbMath Open — the world's most comprehensive reviewed database of mathematical literature.

This server exposes the zbMath Open REST API as Model Context Protocol (MCP) tools, enabling AI assistants such as Claude to search and retrieve mathematical publications, author profiles, and software entries directly.

Tools

Tool	Description
`search_documents`	Free-text search across 4.5 M+ zbMath documents
`get_document`	Fetch full metadata for a document by its zbMath ID
`structured_search`	Field-filtered search (author, title, MSC code, year range, journal)
`get_author`	Fetch an author profile by zbMath author ID
`get_software`	Fetch a software / swMath entry by its numeric ID

Related MCP server: arxiv-reader-mcp

Requirements

Python 3.11+
uv (recommended) or pip

Installation

Using uv (recommended)

Installs a global zbmath-mcp command:

uv tool install git+https://github.com/iwaokimura/zbmath-mcp.git

Using pip

pip install git+https://github.com/iwaokimura/zbmath-mcp.git

From source

git clone https://github.com/iwaokimura/zbmath-mcp.git
cd zbmath-mcp
uv sync

(With plain pip instead of uv, run pip install -e . in place of uv sync.)

Usage

Running the server

If you installed it as a tool (uv) or with pip:

zbmath-mcp

From a source checkout:

uv run zbmath-mcp

The server communicates over stdio using the MCP protocol, so running it in a plain terminal just waits for a client to connect — that is expected. Normally an MCP client (see below) launches it for you.

Connecting with Claude Desktop

Add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "zbmath": {
      "command": "zbmath-mcp"
    }
  }
}

Or, to run from a source checkout without installing (replace the path with your clone location):

{
  "mcpServers": {
    "zbmath": {
      "command": "uv",
      "args": ["--directory", "/path/to/zbmath-mcp", "run", "zbmath-mcp"]
    }
  }
}

Connecting with Claude Code (CLI)

If installed as a command:

claude mcp add zbmath -- zbmath-mcp

Or from a source checkout (replace the path with your clone location):

claude mcp add zbmath -- uv --directory /path/to/zbmath-mcp run zbmath-mcp

Example interactions

Once connected, you can ask an AI assistant:

"Search zbMath for papers on the Langlands program from the last 5 years."
"Get the zbMath document with ID 7192477."
"Find all papers by Euler in zbMath."
"Search for papers in MSC class 11 (Number Theory) published between 2000 and 2010."
"Look up the software entry for Macaulay2 on swMath."

Development

git clone https://github.com/iwaokimura/zbmath-mcp.git
cd zbmath-mcp
uv sync          # installs runtime + dev dependencies
uv run pytest    # run the test suite

License

MIT — see LICENSE.

Available Tools

5 tools

get_authorA

Retrieve profile information for a zbMath author by their profile ID.

Args: author_id: The zbMath author profile identifier string, e.g. "euler.leonhard" or "gauss.carl-friedrich".

Returns: JSON string with the author's profile data including name variants, affiliated institutions, and publication count.

ParametersJSON Schema

Name	Required	Description	Default
`author_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description discloses that the tool returns a JSON string with specific fields (name variants, institutions, publication count), implying a read-only operation. It does not cover error handling or rate limits, but for a simple retrieval, the behavioral implications are clear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with Args and Returns sections, making it easy to parse. It is concise but includes necessary details. It could be slightly more streamlined, but overall it is well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

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, output schema exists), the description covers the key aspects: what it does, what input it needs, and what output to expect. It does not mention error responses, but for a retrieval tool, this is acceptable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides no description for the single parameter 'author_id' (0% coverage), but the description adds valuable examples (e.g., 'euler.leonhard' or 'gauss.carl-friedrich'), making the expected format explicit.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Retrieve', the resource 'profile information for a zbMath author', and the method 'by their profile ID'. It distinguishes from sibling tools like get_document and get_software, which focus on documents and software respectively.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies that the user needs the author ID to use the tool, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it specify any exclusions or prerequisites beyond having the ID.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_documentA

Retrieve full metadata for a single zbMath document by its numeric ID.

Args: zbmath_id: The numeric zbMath document identifier (e.g. 7192477 for Zbl 7192477).

Returns: JSON string with complete document metadata including title, authors, abstract, MSC classification, journal, DOI, review, and links.

ParametersJSON Schema

Name	Required	Description	Default
`zbmath_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A3.7/5.0

Behavior3/5

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 transparently describes the return format as a JSON string with specific fields, but does not disclose error handling, rate limits, or authentication needs. It is adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loaded with purpose, and structured with Args and Returns sections. Every sentence adds value with no redundancies.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With a single parameter, presence of an output schema (though not shown), and clear description of what is returned, the description is largely complete. Minor gap: no differentiation from sibling tools, but the simplicity of the tool mitigates this.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description explains the zbmath_id parameter in detail, providing example and clarifying that it is a numeric identifier. This adds significant meaning beyond the schema definition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves full metadata for a single zbMath document by numeric ID, using the verb 'Retrieve' and specifying the resource. It does not explicitly differentiate from siblings like get_author or search_documents, but the purpose is clear and specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a numeric ID is available and metadata is desired. It does not provide when-not or alternatives explicitly, which would be helpful given sibling tools exist, but the context is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_softwareA

Retrieve metadata for a zbMath / swMath software entry by its numeric ID.

Args: software_id: The numeric swMath software identifier.

Returns: JSON string with software metadata including name, description, programming language, keywords, and references.

ParametersJSON Schema

Name	Required	Description	Default
`software_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A3.9/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries full burden. It correctly states the tool is for reading metadata (non-destructive), but it does not disclose potential error behavior (e.g., invalid ID) or any authentication needs. This is adequate but minimal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loads the purpose, and uses a clear Args/Returns format. Every sentence adds value, though the format is slightly more verbose than necessary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one required parameter, no nested objects, has output schema), the description covers the core functionality, argument, and return fields adequately. It is complete enough for an agent to use without confusion.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaning beyond the input schema by explaining that 'software_id' is 'the numeric swMath software identifier'. The schema only specifies type integer, so the description provides necessary context. Schema coverage is 0%, making this compensation important.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Retrieve' and clearly identifies the resource as 'metadata for a zbMath / swMath software entry by its numeric ID'. This clearly distinguishes it from sibling tools like 'get_author' or 'search_documents'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a numeric software ID is available, but it does not explicitly state when to use this tool versus alternatives. No exclusions or alternative suggestions are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_documentsA

Search zbMath Open for mathematical documents using a free-text query.

Args: query: Free-text search string, e.g. "Riemann hypothesis" or "spectral theory elliptic operators". results_per_page: Number of results to return (1–100, default 10). page: Zero-based page index for pagination (default 0).

Returns: JSON string containing total result count and a list of matching documents, each with id, title, authors, year, journal, MSC codes, a short review excerpt, and a zbMath URL.

ParametersJSON Schema

Name	Required	Description	Default
`page`	No
`query`	Yes
`results_per_page`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.8/5.0

Behavior5/5

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 transparently describes the return format (JSON string with fields) and pagination behavior. The tool is clearly read-only with no destructive effects mentioned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise at three sentences plus a Returns paragraph, well-structured with clear Args/Returns sections. Every sentence adds value with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is comprehensive for a search tool with three parameters and an output schema. It covers query syntax, pagination, result fields, and includes an example. No additional context is needed for correct tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so the description is essential. It thoroughly explains all three parameters, including the free-text nature of query, the range and default for results_per_page, and the zero-based page index. This adds significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches zbMath Open for mathematical documents using a free-text query. It explicitly distinguishes from sibling tools like get_document and structured_search by focusing on free-text search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context with parameter details (query, results_per_page, page) and describes pagination. However, it does not explicitly state when to use this tool versus alternatives, which are sufficiently different to imply usage 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.

structured_searchA

Search zbMath documents using structured field filters.

Use this instead of search_documents when you want to restrict results to specific fields such as author name, MSC subject class, or year range.

Args: author: Author (contributor) name, e.g. "Euler" or "Riemann, B.". title: Words or phrases to match in the document title. msc_code: MSC 2020 classification code, e.g. "11" for Number Theory or "35J15" for a specific code. year_from: Earliest publication year (inclusive). year_to: Latest publication year (inclusive). journal: Journal / bibliographic source name fragment. results_per_page: Number of results (1–100, default 10). page: Zero-based page index for pagination (default 0).

Returns: JSON string with total result count and matching documents.

ParametersJSON Schema

Name	Required	Description	Default
`page`	No
`title`	No
`author`	No
`journal`	No
`year_to`	No
`msc_code`	No
`year_from`	No
`results_per_page`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.8/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses return format (JSON with count and documents) and parameter behavior, but does not explicitly state read-only nature or other side effects. However, search context implies safe operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise and well-structured: one-line purpose, usage guidance, parameter list with examples, and return description. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 8 optional parameters and existence of output schema, the description covers all parameters, usage, and return. It distinguishes from siblings, making it complete for a search tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains all 8 parameters with examples (e.g., author 'Euler', msc_code '11', defaults for results_per_page and page), adding significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs 'Search zbMath documents using structured field filters', with a specific verb and resource. It distinguishes itself from the sibling 'search_documents' by noting it is for restricting results to specific fields.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states 'Use this instead of search_documents when you want to restrict results to specific fields such as author name, MSC subject class, or year range.' This provides clear condition and alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

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TDQS

A4.3/5.0

Disambiguation5/5

Each tool targets a distinct purpose: author profile, document metadata, software metadata, free-text document search, and structured document search. Even the two search tools are clearly differentiated by their query style (free-text vs. field-specific filters).

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in lowercase snake_case (get_author, get_document, get_software, search_documents, structured_search). The convention is uniform and predictable.

Tool Count5/5

With 5 tools, the server is well-scoped for a mathematical reference database. It covers retrieval of three core entity types (author, document, software) and two complementary search modalities (free-text and structured).

Completeness4/5

The tool surface covers essential retrieval and search operations, but lacks dedicated search endpoints for authors or software. While structured_search can filter documents by author, it cannot return author profiles or software entries directly, which is a minor gap.

Maintenance

ActivityStale

ResponsivenessSyncing

Resources

GitHub Repository

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