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Task-oriented MCP for Indonesian law: search, resolve citations, read laws, and MK decisions.
Task-oriented MCP for Indonesian law: search, resolve citations, read laws, and MK decisions.
Remote endpoints: streamable-http: https://mcp.pasal.id/mcp
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
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Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"io-github-aturio-pasal-id-mcp": {
"url": "https://mcp.pasal.id/mcp"
}
}
}From the project's GitHub README.
The first open, AI-native Indonesian legal database. Gives Claude and any MCP-compatible AI assistant grounded, citation-ready access to 100,000+ Indonesian regulations — UU, PP, Perpres, PERMEN, PERDA, and 20+ other regulation types — directly from authoritative sources (peraturan.go.id, BPK JDIH, JDIH MK, JDIHN).
https://mcp.pasal.id/mcpIndonesian law is scattered across dozens of government portals, each with its own PDF quirks and status ambiguities. Most LLM answers about Indonesian regulations are hallucinated — the training data is thin, and the live web isn't indexed for precise legal retrieval.
Pasal.id consolidates 100,000+ regulations into structured data (pasal-level granularity, whole-law hierarchy, preamble sections, amendment history, and legal-status provenance) and exposes it to AI assistants via MCP. Every answer an LLM gives using this server can be grounded in a specific article, regulation part, and authoritative source.
Pick your client. All use the same server URL: https://mcp.pasal.id/mcp.
claude mcp add --transport http pasal-id https://mcp.pasal.id/mcp
Claude Code will open a browser window for OAuth on first use. For CI/automation, use a personal access token from pasal.id/akun:
claude mcp add --transport http pasal-id https://mcp.pasal.id/mcp \
--header "Authorization: Bearer ${PASAL_MCP_TOKEN}"
All consume the same JSON. Paste into the relevant config file:
{
"mcpServers": {
"pasal-id": {
"type": "http",
"url": "https://mcp.pasal.id/mcp",
"headers": {
"Authorization": "Bearer ${PASAL_MCP_TOKEN}"
}
}
}
}
| Client | Config file |
|---|---|
| Claude Desktop | ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) · %APPDATA%\Claude\claude_desktop_config.json (Windows) |
| Cursor | ~/.cursor/mcp.json or .cursor/mcp.json (workspace) |
| Windsurf | ~/.codeium/windsurf/mcp_config.json |
| VS Code MCP | .vscode/mcp.json (workspace) |
| Claude Code | .mcp.json (project root) |
Full per-client walkthrough: docs/clients.md.
Settings → Developer Tools → Add MCP Server → paste https://mcp.pasal.id/mcp.
The server exposes six task-oriented tools to AI assistants (v2.0.0 — the earlier eleven-tool surface keeps working for existing integrations but is deprecated and scheduled for removal after August 2026):
| Tool | Purpose |
|---|---|
search_legal | Find regulations when you do not yet know which law applies — topics, keywords, or messy citations, with validated granular filters (multiple types, year, status, issuing body, region) and diagnostics that explain zero results. |
resolve_law | Turn any reference — "KUHP", "UU 13/2003", "Pergub DKI 220 tahun 2010", a pasted title — into a canonical law_id, or get disambiguation candidates instead of a guess. |
get_law_context | Compact orientation on one law: summary (status, structure counts, top-level outline), a pasal-range-compressed outline, or typed relationship groups (amendments, court reviews) — token-budgeted. |
read_law | Read text with forgiving selectors: pasal 27, pasal 27-30, bab III, menimbang, penjelasan pasal 5, lampiran, all — with cursors, char budgets, and explicit missing reporting. |
search_court_decisions | Search Constitutional Court (Mahkamah Konstitusi) decisions by reviewed law, lane (PUU/SKLN/PHPU/PHPKADA), ruling, year, dissent, or judge. |
report_issue | Report data problems; the search_failure type ("I searched X and expected law Y") feeds the search regression suite directly. |
Every v2 response carries a request_id and structured diagnostics; errors are
typed (error_code + recovery guidance + valid_values) so assistants can
self-correct instead of retrying blindly. The canonical workflow: resolve_law
when you know the law → get_law_context to orient → read_law for text;
search_legal when you don't.
Schemas + example calls: docs/tools.md.
Once connected, ask your AI assistant questions like:
The assistant should search first, retrieve only the needed Pasal or regulation part, verify status/provenance when the answer depends on currency, and use report_issue when the parsed corpus has a real data problem.
Pasal.id itself lives in a private repository — but this repo is public and we welcome:
PRs to the source regulations database happen through the crowd-correction workflow at pasal.id: any user can highlight a passage and suggest a fix; our team reviews and merges within days.
AGPL-3.0 — see LICENSE.
The MCP server code and the regulation data are both open. Attribution is appreciated; commercial derivatives must remain open-source under the same license.
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