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lemma_docs_mcp

by zackscriven

Search Lemma Docs Context

lemma_docs_context
Read-onlyIdempotent

Find ranked excerpts from Lemma's local docs to answer questions about entity accounts, deposit bonuses, fixed fee loans, MSO-PC compliance, and onboarding.

Instructions

Search the local Lemma (getlemma.com) documentation corpus and return focused, ranked source excerpts for a question or task. Lemma is healthcare-practice banking: entity accounts, deposit bonuses, fixed fee loans, cash sweeps, MSO-PC compliant banking guardrails, and shared onboarding. Routes the query into one of three internal namespaces (getting-started: quickstart/onboarding/KYB; guides: deposit bonuses, fixed fee loans, MSO-PC compliance, collaboration, owning multiple entities; product-updates: changelog and roadmap) and returns compact chunks with source paths. This is a local documentation index only — it NEVER calls live Lemma or banking APIs, and it cannot move money or mutate any account state.

Coverage note: the corpus is the 8 pages Lemma exposes as markdown. Banking-operations pages (accounts, cards, transactions, move money), insurance/lockbox, invoicing, team-management, and the API reference are NOT in this index — say so instead of guessing when a query needs them.

Args:

  • query (string, required): The documentation question or task, 2-500 chars.

  • namespace ('auto' | 'getting-started' | 'guides' | 'product-updates', default 'auto'): Corpus area. Use 'auto' unless you already know the area.

  • intent ('answer' | 'build_context' | 'source_map', default 'answer'): How the returned context will be used; adjusts guidance.

  • max_chunks (int 1-12, default 6): Page size.

  • offset (int >= 0, default 0): Ranked matches to skip, for paging.

  • response_format ('markdown' | 'json', default 'markdown'): Text rendering; structured content is always attached.

Returns (structured): { query, namespace, intent, guidance, chunks: [{ id, score, namespace, source_type, path, heading, excerpt, metadata }], pagination: { total_matches, count, offset, has_more, next_offset? }, follow_ups: [string], truncated?, truncation_message?, stats: { indexed_chunks, returned_chunks } }

Chunk excerpts are capped; pass a chunk's id (or its path) to lemma_docs_get for the full text.

Examples:

  • "How does the deposit bonus accrue and when is it paid?" -> guides (deposit-bonuses).

  • "Open an account for a new PLLC" -> getting-started (quickstart, KYB, beneficial owners).

  • "Does Lemma support Zelle?" -> product-updates (roadmap workaround section).

  • "What guardrails does Lemma set up for an MSO-PC structure?" -> guides (mso-pc-compliance).

  • Follow-up paging: repeat the same query with offset=pagination.next_offset.

Errors:

  • "Lemma docs corpus root not found ..." -> set LEMMA_DOCS_CORPUS_ROOT to the absolute path of the lemma-docs-*.md folder and restart.

  • Empty chunks with guidance "No strong ... matches" -> retry with a more specific Lemma term (entity, deposit bonus, fixed fee loan, cash sweep, MSO-PC), or the topic may be outside the 8-page corpus.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe Lemma documentation question or task, e.g. 'How does the deposit bonus accrue?'.
intentNoHow the context will be used: 'answer' a question, 'build_context' for coding/implementation, or 'source_map' to list where sources live.answer
offsetNoNumber of ranked matches to skip, for paging through results (default 0).
namespaceNoCorpus area to search: 'getting-started' (quickstart, onboarding, KYB), 'guides' (deposit bonuses, fixed fee loans, MSO-PC compliance, collaboration, multiple entities), 'product-updates' (changelog, roadmap), or 'auto' to route from the query (default).auto
max_chunksNoMaximum chunks to return per page, 1-12 (default 6).
response_formatNoText output format: 'markdown' for human-readable (default) or 'json' for the full machine-readable object. Structured content is always attached either way.markdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
statsYes
chunksYes
intentYes
guidanceYes
namespaceYes
truncatedNo
follow_upsYes
paginationYes
truncation_messageNo
Install Server

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses important non-obvious behaviors: it is a local documentation index only, never calls live Lemma or banking APIs, cannot move money or mutate state, and excludes specific page areas. It also explains truncation and error conditions, adding substantial behavioral context beyond 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?

Although the description is long, it is well-structured with clear sections (coverage, args, returns, examples, errors) and every sentence contributes actionable information. The core purpose and key constraints are front-loaded before the parameter details.

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 covers the full call contract: parameter semantics, routing behavior, return structure, pagination, examples, error handling, and explicit linkage to the sibling tool. Nothing needed for correct invocation or interpretation is missing.

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%, so the baseline is 3, but the description adds meaningful enrichment: per-namespace examples mapping queries to areas, intent usage examples, a follow-up paging pattern with offset, and clarification of response_format. These examples go beyond the schema's property descriptions.

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: 'Search the local Lemma (getlemma.com) documentation corpus and return focused, ranked source excerpts.' It clearly differentiates from the sibling lemma_docs_get by noting that chunks are capped and that the full text is obtained via lemma_docs_get.

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 explicitly says to use 'auto' unless the corpus area is already known, and it names the sibling tool for retrieving full text. The coverage note instructs the agent to say so instead of guessing when a query falls outside the 8-page index, which is concrete when-not-to-use guidance.

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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