Skip to main content
Glama
Beennnn

openbanking-mcp

by Beennnn

banque_echeances

Identify recurring bank transactions from account history, showing frequency, median amount, and next occurrence date to anticipate upcoming debits and credits.

Instructions

Les opérations qui reviennent (prélèvements ET rentrées), détectées sur l'historique : cadence, montant médian, date du prochain passage. Chacune porte confidence : "sure" (≥3 passages réguliers) ou "faible" (2 passages — une coïncidence possible, à ne pas annoncer comme un fait). annuel_detectable dit si l'historique remonte assez loin pour qu'une échéance annuelle ait pu être vue passer deux fois ; s'il est faux, l'absence de taxe foncière ne prouve RIEN et toute projection est optimiste — le dire, plutôt que conclure que tout va bien. jours_avant_annuel_detectable donne le délai : la banque ne rend que ~90 jours, mais bankread accumule localement, donc ce nombre descend tout seul à chaque lecture.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
compteNoIdentifiant du compte. Omis : le premier compte lié.
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It discloses confidence thresholds ('sure' ≥3 passages, 'faible' for 2), explains that low confidence should not be announced as fact, details the annual detectability limitation (absence of tax foncière proves nothing if history is too short), and notes that bankread accumulates locally extending the ~90-day bank window. This is rich behavioral context beyond basic functioning.

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 well-structured: it opens with the main output, then explains confidence levels, annual detection, and local accumulation in separate clauses. Every sentence adds value, but the technical details make it somewhat long. It is appropriately sized for the complexity without redundancy.

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?

There is no output schema, so the description must convey the return structure. It mentions all key fields (cadence, montant médian, date du prochain passage) and specific metadata (confidence, annuel_detectable, jours_avant_annuel_detectable). It lacks an explicit field list or error conditions, but given the single input parameter and straightforward purpose, the description is sufficiently complete for agent invocation.

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% for the single parameter, which is self-explanatory ('Identifiant du compte. Omis : le premier compte lié.'). The description adds no additional parameter details, but does not need to since the schema already covers it. Baseline 3 is appropriate for high coverage.

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 explicitly states the tool's function: detecting recurring operations (both debits and credits) from history and providing cadence, median amount, and next occurrence date. This is a specific verb+resource (detect recurring operations) and clearly distinguishes it from siblings like transactions or projection.

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 implies when to use it (when you need recurring operation detection) and adds context about historical depth limits. It does not explicitly name alternatives or exclusions, but the sibling tools are distinct enough that this purpose is unambiguous. A clear context is present without explicit when-not guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Beennnn/openbanking-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server