Beancount.io

Read Entry Source Context

getEntryContext

Read-onlyIdempotent

Read the source context around one entry, addressed by the entry_hash listLedgerEntries returns (as entryHash or entry_hash); updateEntrySource and deleteEntrySource take the same hash and this result's sha256sum. Same data as the entry-context resource. A result with generated_from is a copy a plugin or a pad generated from that source entry (amortize_over, forecast, padding): it shares the source's slice and sha256sum, so editing or deleting it would change the source and every other copy; address the generated_from entry instead.

Input Schema

Name	Required	Description
`ledger`	No	Target ledger as owner/name. Required for an unpinned credential; defaults to the credential's ledger restriction.
`entryHash`	No	The entry's hash.
`entry_hash`	No	Alias of entryHash, as list output spells it.

Output Schema

Name	Required	Description	Default
`ok`	Yes
`error`	No
`result`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 26, 2026

addedInput schema / properties / entry_hash

Added value: +{
+  "description": "Alias of entryHash, as list output spells it.",
+  "type": "string"
+}

removedInput schema / required
```
Removed value: -[
-  "entryHash"
-]
```

First observedOct 24, 2026

TDQS

A4.6/5.0

Behavior5/5

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

The annotations already establish read-only, idempotent, non-destructive behavior, and the description adds substantial context beyond them. It explains that a `generated_from` result is a copy sharing the source's slice and sha256sum, so editing or deleting the copy would affect the source and every other copy. That is exactly the kind of side-effect information an agent needs before using the hash with a mutation tool.

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 dense but appropriately sized for the tool's complexity. The core purpose is front-loaded, followed by addressing details and then the `generated_from` warning. Some sentences are packed with multiple constraints, but each carries operational value.

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 tool has an output schema, full input-schema coverage, and rich annotations, so the description does not need to repeat return structure or safety hints. It still covers the critical contextual gaps: hash provenance, alias naming, resource equivalence, and the danger of acting on generated copies. Nothing essential for correct invocation appears 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 parameters are already documented structurally. The description still adds useful semantics by tying `entryHash` and its alias `entry_hash` to listLedgerEntries output and to the mutation tools that consume the same hash, plus the `sha256sum` relationship. It does not add much about the `ledger` parameter, but the schema covers that.

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 states a specific verb and resource: 'Read the source context around one entry.' It distinguishes this tool by explaining the entry-hash addressing returned by listLedgerEntries and ties the same hash to updateEntrySource and deleteEntrySource, making its role clear against ledger-level siblings.

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 gives clear usage context: get the hash from listLedgerEntries output, and use the same hash for updateEntrySource or deleteEntrySource. It also provides an important exclusion for generated entries by telling the agent to address the `generated_from` entry instead, though it does not explicitly contrast this tool with the entry-context resource.

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

All Beancount.io tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.