MCP server: reconcile ISO 20022 camt.053 statements against expected pain.001 payments -- explainable exact, partial, one-to-many and many-to-one matching.
claude mcp add reconcile-mcp -- uvx reconcile-mcp{
"mcpServers": {
"reconcile-mcp": {
"command": "uvx",
"args": ["reconcile-mcp"]
}
}
}MCP Servers overview
# reconcile-mcp: An MCP Server for ISO 20022 Cash Reconciliation
**A [Model Context Protocol][mcp] server that matches *expected* payments
(from `pain.001` credit transfers) against *observed* booked entries (from a
`camt.053` statement) and returns an explainable reconciliation** — exact
matches, short/over payments, split settlements (one-to-many), batch credits
(many-to-one), and the residual unmatched items on each side, every match
carrying a score and the reasons it was made.
> **Latest release: v0.0.1** — 7 MCP tools over stdio, pure-Python matching
> engine, deterministic sandbox test-mode, for Python 3.10+. Part of the
> [ISO 20022 MCP suite](#the-iso-20022-mcp-suite): you own both sides of the
> match.
## Why this exists
Reconciliation is the treasury team's daily pain: did the money we *expected*
actually *arrive*, and which invoice does each credit belong to? It is rarely
one-to-one — customers underpay, settle an invoice in instalments, or a payout
aggregator sends one lump covering a dozen receivables. `reconcile-mcp` does
this matching as an agent tool, and — critically for finance — **shows its
work**: every pairing comes with a numeric score and a plain list of the
signals (reference, amount, date, counterparty) that drove it.
## The ISO 20022 MCP Suite
`reconcile-mcp` is the **reconciliation workflow** of eight coordinated,
vendor-neutral MCP servers that together cover the ISO 20022 bank-statement
workflow and the November 2026 structured-address cutover, plus a high-level orchestration layer — readiness scoring, clearing-profile linting, and audit evidence — statement depth,
whole-catalogue routing, reconciliation, multi-format ingestion, and address
remediation. Dependency ranges are kept aligned across the suite,
so the servers co-install cleanly in a single Python environment: start with
one, add the rest as your workflow grows.
| Server | Scope | Surface | Install | Use it when |
| --- | --- | --- | --- | --- |
| [`camt053-mcp`][camt053-mcp] | ISO 20022 `camt.053`/`camt.052` bank statements: parse, validate, filter, reverse; MT940/MT942 migration; CBPR+ readiness; journal export | 22 MCP tools · 4 prompts · 3 resources | `pip install camt053-mcp` | You work with bank-to-customer statements end to end — the suite's flagship |
| [`iso20022-mcp`][iso20022-mcp] | Unified gateway: `search` / `describe` / `validate` / `generate` / `parse` meta-tools routed across the `pain` · `pacs` · `camt` · `acmt` families | 7 meta-tools | `pip install "iso20022-mcp[all]"` | You want one entry point to every message family |
| [`reconcile-mcp`](#install) | Matches expected `pain.001` payments against observed `camt.053` entries — exact, partial, one-to-many, many-to-one, every match scored and explained | 7 MCP tools | `pip install reconcile-mcp` | You need explainable statement/payment reconciliation — **this package** |
| [`bankstatementparser-mcp`][bsp-mcp] | Multi-format statement ingestion: ISO 20022 CAMT.053 and pain.001, SWIFT MT940, OFX/QFX, CSV | 5 MCP tools · 1 prompt · 1 resource | `pip install bankstatementparser-mcp` | Your statements arrive in mixed or legacy formats |
| [`structured-address-fix-mcp`][saf-mcp] | ISO 20022 postal-address classification, assessment & remediation for the November 2026 structured-address cutover (`pacs.008` / `pain.001` debtor & creditor addresses) | 9 MCP tools | `pip install structured-address-fix-mcp` | You need debtor/creditor addresses cliff-ready ahead of 14 Nov 2026 |
| [`iso20022-readiness-suite-mcp`](https://github.com/sebastienrousseau/iso20022-readiness-suite-mcp) | Orchestration gateway: detect → structurally validate → clearing-profile lint → readiness score, plus automated remediation and `pacs.002` bank-response simulation — a meta-client over the foundational servers | 4 MCP tools | `pip install iso20022-readiness-suite-mcp` | You want one high-level readiness / orchestration entry point over the suite |
| [`iso20022-bank-profile-mcp`](https://github.com/sebastienrousseau/iso20022-bank-profile-mcp) | Manages, validates and serves bank-specific clearing profiles / rule packs (CBPR+, SEPA_Instant, FedNow, Generic); premium rule-pack entitlement gating | 4 MCP tools | `pip install iso20022-bank-profile-mcp` | You lint payments against your own institution's market practice |
| [`iso20022-evidence-pack-mcp`](https://github.com/sebastienrousseau/iso20022-evidence-pack-mcp) | Compiles readiness findings, remediation diffs and simulated responses into a sealed, Ed25519-signable audit evidence pack | 6 MCP tools | `pip install iso20022-evidence-pack-mcp` | You need tamper-evident audit / certification artifacts |
In one line each: **`camt053-mcp`** is the bank-statement flagship (deepest
camt.05x surface, stdio + authenticated streamable HTTP);
**`iso20022-mcp`** is the generic message toolkit (a handful of verbs over
the whole catalogue); **`reconcile-mcp`** is the reconciliation workflow
(did the money we expected actually arrive?);
**`bankstatementparser-mcp`** is the ingestion layer (many formats in, one
transaction shape out); and **`structured-address-fix-mcp`** is the
postal-address specialist (debtor/creditor addresses cliff-ready for the
Nov 2026 cutover).
The suite also includes per-family servers — [`pain001-mcp`][pain001-mcp]
(credit transfer initiation), [`pacs008-mcp`][pacs008-mcp] (FI-to-FI credit
transfers), and [`acmt001-mcp`][acmt001-mcp] (account management) — whose
parsed output feeds straight into this server's `normalize_*` adapters.
## Install
```sh
pip install reconcile-mcp
# or run without installing:
uvx reconcile-mcp
```
MCP client config (e.g. Claude Desktop `claude_desktop_config.json`):
```json
{
"mcpServers": {
"reconcile": {
"command": "reconcile-mcp"
}
}
}
```
## Quick start (zero real data)
The server ships a **sandbox test-mode**: deterministic scenarios so you can
run the whole flow with no setup and no real cash data. One call gets you a
full, explainable result:
```
run_sandbox_scenario(name="month_end")
```
returns a realistic mixed close — one clean match, one short payment, one split
settlement, and an unexpected credit correctly left unmatched:
```jsonc
{
"summary": {
"expected_count": 3, "observed_count": 5,
"matched_expected": 3, "unmatched_observed": 1,
"matches_by_type": {"exact": 1, "amount_mismatch": 1, "one_to_many": 1},
"fully_reconciled": false
},
"matches": [
{"type": "amount_mismatch", "expected": ["INV-6002"], "observed": ["ENT-52"],
"amount_delta": "-99.99", "confidence": "high",
"reasons": ["reference exact", "amount close (delta -99.99)", "date +/-0d", "counterparty exact"]},
{"type": "exact", "expected": ["INV-6001"], "observed": ["ENT-51"], "amount_delta": "0.00"},
{"type": "one_to_many", "expected": ["INV-6003"], "observed": ["ENT-53", "ENT-54"],
"reasons": ["amount sum of 2 entries"]}
],
"unmatched_observed": ["ENT-55"]
}
```
List every scenario with `list_sandbox_scenarios`; load one to inspect or edit
its inputs with `load_sandbox_scenario`.
## Bring your own data
Records are small canonical objects — `id` and `amount` required, everything
else optional and used to sharpen matching:
```jsonc
{
"id": "INV-1001", // your reference / end-to-end id
"amount": 1200.00,
"currency": "EUR", // ISO 4217
"date": "2026-03-02", // ISO-8601
"counterparty": "Acme Ltd",
"reference": "INV-1001" // remittance / structured reference
}
```
Already using the rest of the suite? Feed parsed output straight in — the
adapters map it for you:
- `normalize_pain001(document)` → the *expected* side, from
[`pain001-mcp`][pain001-mcp].
- `normalize_camt053(document)` → the *observed* side, from
[`camt053-mcp`][camt053-mcp].
Then call `reconcile(expected, observed)`.
## Tools
- `reconcile` — Match expected payments against observed entries; full explainable report.
- `explain_match` — Score a single expected/observed pair with a per-signal breakdown (tuning aid).
- `normalize_pain001` — Adapt parsed `pain.001` output into canonical *expected* records.
- `normalize_camt053` — Adapt parsed `camt.053` output into canonical *observed* records.
- `list_sandbox_scenarios` — List the built-in test-mode scenarios and magic references.
- `load_sandbox_scenario` — Return one scenario's expected/observed inputs to inspect or edit.
- `run_sandbox_scenario` — Load a scenario and reconcile it in one call — the fastest first run.
## How matching works
Each candidate pair is scored on four weighted signals, then classified:
- **Reference** (0.45) — exact / partial equality of references and end-to-end
ids, normalised to bare alphanumerics.
- **Amount** (0.35) — exact within tolerance, or a linearly-decaying closeness
with the delta reported.
- **Date** (0.10) — proximity within a configurable window; neutral if unknown.
- **Counterparty** (0.10) — token-set overlap of names; neutral if unknown.
Assignment is greedy, highest-score-first and fully deterministic (a total
tiebreak order), so the same inputs always produce the same result. Residuals
are then tested for **one-to-many** (a bounded subset-sum: one expected settled
by several entries) and **many-to-one** (one entry covering several expected).
Tune any of it via the `options` argument: `abs_tol` / `rel_tol`,
`date_window_days`, `high_threshold`, `review_threshold`, `currency_strict`,
`enable_one_to_many`, `max_combination`.
## Development
```sh
git clone https://github.com/sebastienrousseau/reconcile-mcp
cd reconcile-mcp
python -m venv .venv && . .venv/bin/activate
pip install -e . && pip install pytest pytest-cov ruff black mypy
pytest # 100% branch coverage gate
ruff check reconcile_mcp tests && black --check reconcile_mcp tests && mypy reconcile_mcp
```
## Licence
Licensed under the [Apache License, Version 2.0](LICENSE).
---
`mcp-name: io.github.sebastienrousseau/reconcile-mcp`
[mcp]: https://modelWhat people ask about reconcile-mcp
What is sebastienrousseau/reconcile-mcp?
+
sebastienrousseau/reconcile-mcp is mcp servers for the Claude AI ecosystem. MCP server: reconcile ISO 20022 camt.053 statements against expected pain.001 payments -- explainable exact, partial, one-to-many and many-to-one matching. It has 0 GitHub stars and was last updated today.
How do I install reconcile-mcp?
+
You can install reconcile-mcp by cloning the repository (https://github.com/sebastienrousseau/reconcile-mcp) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is sebastienrousseau/reconcile-mcp safe to use?
+
sebastienrousseau/reconcile-mcp has not been audited yet by our security agent. Review the original repository on GitHub before using it in production.
Who maintains sebastienrousseau/reconcile-mcp?
+
sebastienrousseau/reconcile-mcp is maintained by sebastienrousseau. The last recorded GitHub activity is from today, with 2 open issues.
Are there alternatives to reconcile-mcp?
+
Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.
Deploy reconcile-mcp to your cloud
Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.
Maintain this repo? Add a badge to your README
Drop the badge into your GitHub README to show it's tracked on ClaudeWave. Each badge links back to this page and reflects the live Trust Score.
[](https://claudewave.com/repo/sebastienrousseau-reconcile-mcp)<a href="https://claudewave.com/repo/sebastienrousseau-reconcile-mcp"><img src="https://claudewave.com/api/badge/sebastienrousseau-reconcile-mcp" alt="Featured on ClaudeWave: sebastienrousseau/reconcile-mcp" width="320" height="64" /></a>More MCP Servers
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
An open-source AI agent that brings the power of Gemini directly into your terminal.
The fastest path to AI-powered full stack observability, even for lean teams.
Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface
🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!