What can you do with this server?

This server provides access to Japan's official e-Gov law database, enabling search and retrieval of national legislation with verifiable citations. No API key is required. * Search laws by title (jp_search_laws): Find laws using a partial or full Japanese title (e.g., "民法"), returning up to 100 results with law IDs, numbers, types, and promulgation dates. * Full-text keyword search (jp_search_by_keyword): Search across all laws for a keyword (e.g., "個人情報"), with highlighted snippets and pagination support. * Fetch law metadata (jp_get_law): Retrieve metadata for a specific law by law_id — title, law number, type, promulgation date, and amendment details — without the full body text. * Fetch a specific article (jp_get_article): Retrieve the text of a single article using a law_id and article number (e.g., "3_2" for branch articles). * Fetch full law text (jp_get_full_text): Retrieve the complete text of a law, truncated at ~300,000 characters for large laws, with a truncated flag and byte size included. Every response includes: * A stable e-Gov viewer URL (eli_uri) as a durable identifier * A human-readable citation (e.g., 民法（明治二十九年法律第八十九号）) * A machine-readable API source URL (source_url) for independent verification * A dataset note with source attribution from Japan's official open data portal All tool calls are recorded in an audit log for transparency.

How do I use jp-eli-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., "@jp-eli-mcp search for the Japanese Civil Code" 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.

jp-eli-mcp

by matematicsolutions

Overview Schema Related Servers Score Discussions

Python

Remote

jp-eli-mcp

An MCP server for Japan's official e-Gov law search API (laws.e-gov.go.jp), run by the Digital Agency. It searches, fetches, and cites national legislation - acts, cabinet orders, ministerial ordinances - with a verifiable citation on every response.

Part of the MateMatic eu-legal-mcp production line, extended into Asia. Same citation contract (a stable identifier + a human-readable citation + a source URL) as the 18 EU/EEA connectors, adapted for a jurisdiction with no ELI scheme.

Scope. Discovery is by law title (jp_search_laws) or full-text keyword (jp_search_by_keyword); fetch a specific article (jp_get_article) or the full text (jp_get_full_text, truncated for very large laws such as the Civil Code). Every response carries a dataset_note.
Licence. e-Gov law data is official public information published by the Japanese government as open data (keyless, REST/JSON). This connector relays it with attribution and a source_url.

The tools

Tool	What it does
`jp_search_laws`	Search laws by (partial) title.
`jp_search_by_keyword`	Full-text search across all laws, with highlighted snippets.
`jp_get_law`	Metadata for a law by `law_id`: title, law number, promulgation date.
`jp_get_article`	The text of one article of a law, by `law_id` and `article_num`.
`jp_get_full_text`	The full text of a law (truncated at ~300,000 characters).
`jp_coverage`	Declare what this connector covers, when each family was captured, and - explicitly - what it does NOT cover. Every gap carries a fallback.

Every response carries the contract: eli_uri (Japan has no ELI - this is the durable e-Gov viewer URL, e.g. https://laws.e-gov.go.jp/law/129AC0000000089, see eli_note), human_readable_citation (e.g. 民法（明治二十九年法律第八十九号）), and source_url (the machine-readable API URL).

Related MCP server: e-Gov Law MCP Server

Install

Not yet on PyPI - install from source until the first release ships:

git clone https://github.com/matematicsolutions/jp-eli-mcp
cd jp-eli-mcp
pip install -e .

Once released, this will be uvx jp-eli-mcp.

Configuration via env:

JP_ELI_BASE_URL - default https://laws.e-gov.go.jp/api/2
JP_ELI_CACHE_DIR - default ~/.matematic/cache/jp-eli
JP_ELI_AUDIT_DIR - default ~/.matematic/audit

No API key. e-Gov's law search API is keyless.

Configure (Claude Code / any MCP client)

{
  "mcpServers": {
    "jp-eli-mcp": { "command": "jp-eli-mcp" }
  }
}

Windows 11 with Smart App Control

Smart App Control blocks unsigned executables, which covers uvx.exe, pip.exe and the jp-eli-mcp.exe launcher that pip writes at install time. The python.exe and py.exe from the python.org installer are signed by the Python Software Foundation, so running the module through the interpreter works:

python -m pip install jp-eli-mcp
python -m jp_eli_mcp

pip.exe is blocked for the same reason, so install with python -m pip, not pip install. If python is not on PATH, use the Windows launcher: py -3 -m jp_eli_mcp.

{ "mcpServers": { "jp-eli-mcp": { "command": "python", "args": ["-m", "jp_eli_mcp"] } } }

Do not turn Smart App Control off to work around this - it cannot be re-enabled without reinstalling Windows.

Governance

Public data only - read-only against e-Gov; no client data leaves the machine.
Audit log - every tool call appends one JSON line to ~/.matematic/audit/jp-eli-mcp.jsonl.
Vendor-neutral - talks only to laws.e-gov.go.jp; no LLM provider, no telemetry.
Verifiable citations - every response is independently checkable via source_url.

See CONSTITUTION.md and DISCOVERY.md.

Tests

pip install -e ".[dev]"
pytest tests/test_instructions_drift.py -v   # offline
pytest tests/test_smoke.py -v                # hits live e-Gov

Licence

Apache-2.0. © Matematic Solutions / Wieslaw Mazur.

Available Tools

6 tools

jp_coverageA

Read-onlyIdempotent

Declare what this connector covers, how it is sourced, and what it does NOT cover.

Call this before telling a user that the law "does not contain" something, and whenever a search comes back empty: the absence may be a gap in this connector rather than in the law. Every gap carries a fallback saying where to look instead.

Returns: Coverage with families, an as-of note, and a non-empty list of known gaps.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

Output Schema

ParametersJSON Schema

Name	Required	Description
`status`	No
`families`	No
`as_of_note`	Yes	States what the dates mean, and what they do not promise.
`known_gaps`	No	Never empty. An empty list would mean 'not checked', not 'no gaps'.

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already establish read-only, idempotent, open-world behavior. The description adds valuable context by warning that a missing result may be a connector gap rather than an absence in the law, and by summarizing the returned Coverage object. It does not contradict the annotations.

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 compact and well-structured: purpose first, then precise usage triggers, then a one-line return summary. Every sentence earns its place and nothing is repeated from the annotations or schema.

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?

For a zero-parameter, read-only metadata tool with an output schema, the description fully covers what the tool does, when to invoke it, why it matters, and what to expect in the response. An agent has enough context to use it correctly alongside the sibling search tools.

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 tool has zero parameters and the schema fully covers this with an empty object, so the baseline is 4. No parameter-level detail is needed, and the description appropriately focuses on return semantics instead.

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 opens with a specific verb and resource: 'Declare what this connector covers, how it is sourced, and what it does NOT cover.' It clearly distinguishes this coverage/metadata tool from the sibling search and retrieval tools by focusing on connector gaps rather than legal text.

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?

The description gives explicit trigger conditions: call before telling a user the law 'does not contain' something, and whenever a search comes back empty. It also explains the reasoning and tells the agent that every gap carries a fallback, so the next step is clear.

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

jp_get_articleA

Read-onlyIdempotent

Fetch the text of one article of a law.

ParametersJSON Schema

Name	Required	Description	Default
`law_id`	Yes	e.g. ``"129AC0000000089"`` (the Civil Code).
`article_num`	Yes	the e-Gov ``Num`` attribute, e.g. ``"1"`` for Article 1, ``"3_2"`` for a branch article (第三条の二).

Output Schema

ParametersJSON Schema

Name	Required	Description
`text`	No
`law_id`	Yes
`caption`	No
`eli_uri`	No
`eli_note`	No
`source_url`	No
`article_num`	Yes
`dataset_note`	No
`human_readable_citation`	No

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds no extra behavioral context beyond stating the read 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?

Single sentence, no redundancy, direct statement of purpose.

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?

Simple tool with full annotations and output schema; description is adequate. Could optionally mention return format, but output schema covers that.

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

Parameters3/5

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

Schema coverage is 100% with clear parameter descriptions. Description adds no additional meaning beyond what schema provides.

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?

Description uses specific verb 'Fetch' and resource 'text of one article of a law'. Clearly distinguishes from siblings like jp_get_full_text which fetches entire law text, and search tools.

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?

No explicit when/when-not guidance in description. Context from sibling names provides implicit differentiation, but description lacks direct usage instructions.

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

jp_get_full_textA

Read-onlyIdempotent

Fetch the full text of a law by law_id. Large laws are truncated.

ParametersJSON Schema

Name	Required	Description	Default
`law_id`	Yes	e.g. ``"129AC0000000089"`` (the Civil Code).

Output Schema

ParametersJSON Schema

Name	Required	Description
`law_id`	Yes
`content`	No
`eli_uri`	No
`eli_note`	No
`byte_size`	No
`truncated`	No
`source_url`	No
`dataset_note`	No
`human_readable_citation`	No

TDQS

A4/5.0

Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. Description adds the important behavioral detail that large laws are truncated, which is beyond annotation coverage.

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?

Two sentences, front-loaded with purpose, no superfluous text. Every word earns its place.

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 an output schema present, description need not explain return values. It covers the main nuance (truncation) and leaves parameter details to schema. Adequate for a simple tool.

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

Parameters3/5

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

Schema description coverage is 100% with an example value for law_id. Description adds no further parameter 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?

Clearly states it fetches the full text of a law by law_id, with a key behavioral note on truncation. Distinguishes from siblings like jp_get_article (single article) and search tools.

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?

Implied usage for fetching full text, but lacks explicit when-not-to-use or comparisons with sibling tools. The truncation note is helpful but not a full guideline.

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

jp_get_lawA

Read-onlyIdempotent

Fetch metadata for a law by its e-Gov law_id (no body text).

ParametersJSON Schema

Name	Required	Description	Default
`law_id`	Yes	e.g. ``"129AC0000000089"`` (the Civil Code).

Output Schema

ParametersJSON Schema

Name	Required	Description
`law_id`	Yes
`eli_uri`	No
`law_num`	No
`eli_note`	No
`law_type`	No
`law_title`	No
`source_url`	No
`dataset_note`	No
`amendment_law_id`	No
`promulgation_date`	No
`human_readable_citation`	No
`amendment_enforcement_date`	No

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already indicate read-only, non-destructive, idempotent. Description adds that only metadata (not body text) is returned, which is useful beyond annotations, but no other behaviors (e.g., error handling) are disclosed.

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?

Single sentence, front-loaded with verb and resource, no redundant words. Efficient and clear.

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 presence of an output schema (not shown but noted), the description is mostly complete. Could mention what metadata includes, but output schema likely compensates.

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

Parameters3/5

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

Schema covers 100% of the single parameter with a good description. Tool description repeats the parameter name and format, adding minimal extra semantics. Baseline 3 met.

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?

Description clearly states 'Fetch metadata for a law' using a specific identifier, and explicitly distinguishes from body text, differentiating it from sibling tools like jp_get_full_text.

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?

Description implies usage for metadata only, but does not explicitly say when to use this tool over siblings (e.g., jp_get_full_text for body text). No when-not advice provided.

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

jp_search_by_keywordA

Read-onlyIdempotent

Full-text search across all Japanese laws for a keyword.

ParametersJSON Schema

Name	Required	Description
`limit`	No	max results, 1-100 (default 10).
`offset`	No	pagination offset (default 0).
`keyword`	Yes	e.g. ``"個人情報"`` (personal information).

Output Schema

ParametersJSON Schema

Name	Required	Description
`items`	No
`keyword`	Yes
`next_offset`	No
`total_count`	Yes
`dataset_note`	No

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, so the agent knows it's a safe, non-destructive read operation. The description adds the key behavioral context of 'full-text search across all Japanese laws', which beyond the annotations specifies the scope and type of search.

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 a single, concise sentence that front-loads the core purpose ('full-text search') and resource ('all Japanese laws'). No extraneous information; every word earns its place.

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 that an output schema exists (not shown but indicated by context), the description does not need to explain return values. It covers the essential purpose and scope. Minor missing details like result ordering or language of keywords are acceptable for a search tool with an output schema.

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

Parameters3/5

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

Schema description coverage is 100% with all three parameters (keyword, limit, offset) already well-documented in the schema. The description does not add additional meaning or constraints beyond what the schema provides, so a baseline score of 3 is appropriate.

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 a full-text search across all Japanese laws for a keyword, using a specific verb ('search') and resource ('all Japanese laws'). This distinguishes it from sibling tools like jp_get_article or jp_get_full_text which are retrieval operations, not searches.

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 does not explicitly state when to use this tool versus alternatives (e.g., jp_search_laws). While the name implies keyword search, there is no guidance on when not to use it or which sibling tool is better for other scenarios. The usage context is implied but not made explicit.

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

jp_search_lawsA

Read-onlyIdempotent

Search Japanese laws by (partial) title.

ParametersJSON Schema

Name	Required	Description	Default
`limit`	No	max results, 1-100 (default 10).
`law_title`	Yes	e.g. ``"民法"`` (Civil Code) or ``"個人情報の保護に関する法律"``.

Output Schema

ParametersJSON Schema

Name	Required	Description
`items`	No
`query`	Yes
`total_count`	Yes
`dataset_note`	No

TDQS

A4.1/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds no further behavioral traits (e.g., rate limits, pagination, or result details). It is adequate but not adding value beyond the annotations.

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 a single, concise sentence that conveys the essential purpose without any extraneous words. It is perfectly sized for a simple search tool.

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 the tool's simplicity, the description and schema are sufficient. An output schema exists (indicated in context signals), and annotations cover safety. The description provides complete context for selecting and invoking this tool correctly.

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?

Schema coverage is 100%, with both parameters described. The description adds concrete examples for law_title (e.g., '民法' and '個人情報の保護に関する法律'), helping an agent understand the format and expected values. This adds meaningful context 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 Japanese laws by (partial) title. The verb 'search' and resource 'Japanese laws' are explicit, and the method 'by (partial) title' distinguishes it from sibling tools like jp_search_by_keyword.

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?

No explicit when-to-use or when-not-to-use guidance is given. The description does not mention alternatives or context. However, the sibling tool names hint at different uses, so an agent can infer but the description itself offers no direct guidance.

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.

1 tool updatev0.3.3Aug 28, 2026
- Addedjp_coverage
5 tool updatesv0.1.0Jul 6, 2026
- First observedjp_get_article
- First observedjp_get_full_text
- First observedjp_get_law
- First observedjp_search_by_keyword
- First observedjp_search_laws

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4.2/5.0

Disambiguation5/5

Each tool targets a distinct operation: searching by title vs. full-text, fetching metadata vs. a single article vs. full text, and declaring coverage. No two tools overlap in purpose.

Naming Consistency5/5

All tools follow the consistent pattern jp_<verb>_<noun>, with search/get as verbs and clear nouns. jp_coverage is a slight exception but still fits the jp_ prefix and is a declarative tool, so the pattern remains predictable.

Tool Count5/5

Six tools is well-scoped for a Japanese law retrieval server: two search methods, three retrieval levels (metadata, article, full text), and an explicit coverage declaration. No excess or deficiency.

Completeness4/5

The core workflows—searching and retrieving law text—are covered. The full-text tool truncates large laws, but jp_coverage explicitly discloses gaps and fallbacks, making the surface reasonably complete for read-only legal access.

Maintenance

ActivityMaintained

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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