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DERO MCP Server

by io.github.DHEBP

dero_docs_get_page

Read-only

Get a single bundled docs page by slug, with plain-text content and headings.

When to call: AFTER dero_docs_search has returned a candidate slug, OR when you have a known slug from a prior citation. PREFER dero_docs_search first when you only have a topic in mind.

Input Requirements (CRITICAL):

  • slug MUST be a non-empty doc slug relative to pages/ (e.g. rpc-api/daemon-rpc-api, tutorials/first-app, dero-pay/quick-start).

  • product is OPTIONAL but RECOMMENDED to disambiguate identical slugs across docs sites (derod, tela, hologram, deropay).

  • offset is OPTIONAL. Long pages (the Captain archive, deep RPC references) are returned in 60000-char chunks; if content_truncated is true in the response, call again with offset: next_offset to fetch the next chunk.

Output: { product, slug, title, headings, content, content_offset, content_length, content_truncated, next_offset, canonical_url, last_updated, source_path }. content_length is the total page size; content_truncated + next_offset signal whether to paginate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesDoc slug relative to pages/ (e.g., "rpc-api/daemon-rpc-api", "tutorials/first-app", "dero-pay/quick-start")
offsetNoByte offset into the page plaintext. Use 0 (or omit) for the first chunk; pass next_offset from a prior response to continue reading a long page.
productNoOptional product scope to disambiguate duplicate slugs

TDQS

A5/5.0
Behavior5/5

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

Describes the return content (title, headings, plain-text content) and the chunking behavior (60000-char chunks, content_truncated flag, next_offset for pagination). Output field list and semantics are fully explained, leaving no ambiguity about 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.

Conciseness5/5

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

Structured with clear sections: purpose, when-to-call, input requirements, output. Front-loaded with the core purpose. Every sentence contributes value; no redundant or vague phrasing. The length is appropriate for the complexity.

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 no output schema, the description fully enumerates the output fields and explains their meaning (content_length, content_truncated, next_offset). It also ties into the broader docs workflow by referencing search and prior citations, covering both typical and edge cases (pagination).

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 covers parameters with details like minLength and enums. The description adds critical behavioral context: slug must be relative to pages/, product is 'RECOMMENDED to disambiguate identical slugs', and offset's chunking protocol is explicitly explained with 60000-char limit and pagination logic. This adds substantial 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 verb ('Get') and resource ('a single bundled docs page by slug'), with added context about content type ('plain-text content and headings'). It distinguishes from siblings like dero_docs_search and dero_docs_list by emphasizing the direct retrieval via slug.

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?

Explicit when-to-call guidance: 'AFTER dero_docs_search has returned a candidate slug, OR when you have a known slug from a prior citation. PREFER dero_docs_search first when you only have a topic in mind.' Also covers pagination handling with offset, making usage unambiguous.

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

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TDQS

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, with detailed descriptions that specify when to call it and how it differs from similar tools. Composite tools are well-defined, overlapping concerns are minimized.

Naming Consistency4/5

Tool names follow a general pattern: 'dero_' for core daemon RPC wrappers, 'tela_' for TELA-specific composites, and descriptive names for other composites. While mostly consistent, there are exceptions like 'audit_chain_artifact_claim' and 'dero_durl_to_scid' breaking the pattern slightly.

Tool Count4/5

With 32 tools, the server is comprehensive but slightly heavy. However, each tool serves a specific need in the DERO ecosystem, covering chain queries, docs, TELA, and composite analyses. The count is justifiable given the domain breadth.

Completeness4/5

The tool set covers core chain operations, documentation, TELA app lifecycle, and common analytical tasks. Minor gaps exist, such as lack of wallet interaction tools or transaction submission, but these are outside the apparent read-only/analysis scope.

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