abap-mcp

Make your AI coding agent an expert SAP ABAP & RAP consultant — local by default. No SAP system, no credentials, one command to install.

abap-mcp is a Model Context Protocol server that gives any AI coding agent — Claude Code, GitHub Copilot, Cursor, Codex, Windsurf — real ABAP senses, built on abaplint (the open-source ABAP parser/linter). The agent brings the reasoning; abap-mcp brings ground truth: a deterministic parser, objective scores, and validated generators that keep the AI honest. It works on ABAP source wherever your agent works — a git checkout, an abapGit export, a code review, CI — long before anything reaches a system.

New to ABAP or RAP? Your agent becomes the senior consultant looking over your shoulder: every snippet linted against Clean ABAP as you write (lint_abap), every finding explained with its rationale and examples (explain_abap_rule), and scaffold_rap_bo starts you from a canonical, self-validated RAP business object instead of a blank editor.
Senior ABAP consultant? It's your assessment and task engine: point your agent at a repo and get a scored, categorized ABAP Cloud readiness report with an A–D tech-debt grade (check_cloud_readiness), a phased migration backlog with efforts and exit criteria (plan_cloud_migration), an objective before/after verdict on every rework (compare_abap), released-API replacements (check_released_api), and CI gates that hold the line while the migration proceeds.

The default stdio edition is 100% local: the analysis engine makes zero network calls and reads no user files. Sources go in as text and structured findings come back. The released-API list and abaplint rule data are package-bundled. An optional guarded Streamable HTTP edition makes the same tools available to remote clients such as ChatGPT web; in that mode, source text is sent to the machine you host. See privacy and data handling.

Why this exists

Every other ABAP MCP server is either a bridge to a live SAP system (ADT/RFC — needs credentials, a system, and trust) or a documentation search. But AI coding agents spend most of their time where the files are — editing abapGit repos, reviewing diffs, generating code — long before anything reaches a system. This server gives agents the missing feedback loop at that layer:

"Does this ABAP parse? Is it clean? How does it perform?" → lint_abap (+ focus packs)
"Fix this block automatically — casing, obsolete syntax." → fix_abap (deterministic, parser-guaranteed)
"How far is this classic report from ABAP Cloud? Grade it." → check_cloud_readiness (A–D)
"Plan the migration — what do we tackle first?" → plan_cloud_migration (phased backlog)
"This class has no tests — start me a harness." → scaffold_abap_unit (failing-by-default)
"What depends on what? Migrate which object first?" → get_object_dependencies (+ Mermaid)
"Did this rework make the code better or worse?" → compare_abap
"Is MARA a released API? What do I use instead?" → check_released_api
"Start me a correct RAP business object." → scaffold_rap_bo
"What's in this 4,000-line class? Draw it." → get_abap_outline (+ Mermaid)

Install — 60 seconds

The only requirement is Node.js 20+. No SAP system, no credentials, no API keys. New to AI tooling (or ABAP)? Follow the from-zero walkthrough in docs/INSTALL.md — or let the installer do it:

Terminal

npx abap-mcp setup     # detects VS Code / Claude Code and registers the server; guides Eclipse

Otherwise, pick your client:

Codex CLI · Codex IDE extension · ChatGPT desktop — one command configures all three on the same Codex host:

bash

codex mcp add abap-mcp -- npx -y abap-mcp

Restart ChatGPT desktop or the IDE extension, then use /mcp to confirm abap-mcp is connected. In ChatGPT desktop you can alternatively open Settings → MCP servers → Add server, choose STDIO, and enter command npx with arguments -y abap-mcp.

Codex plugin (MCP server + review/mentor/migration skills)

bash

codex plugin marketplace add palimkarakshay/abap-mcp
codex plugin add abap-mcp@abap-mcp

ChatGPT web cannot start a local npx process. It needs a deployed HTTPS /mcp endpoint or a secure development tunnel. This repository ships the HTTP entry point and hardening controls, but does not operate a public service. Follow the OpenAI setup and self-hosting guide.

Claude Code

Terminal

claude mcp add abap-mcp -- npx -y abap-mcp

VS Code (Copilot agent mode) — one click on the Install in VS Code badge above, or one command:

bash

code --add-mcp '{"name":"abap-mcp","command":"npx","args":["-y","abap-mcp"]}'

For a whole team, commit examples/vscode/mcp.json as .vscode/mcp.json in your abapGit repo — everyone who opens the folder gets the server offered automatically.

Eclipse (via the GitHub Copilot plugin) — Copilot Chat in Eclipse speaks MCP: open the Copilot menu → Edit preferences → MCP, and add the same "abap-mcp" server block (command npx, args ["-y", "abap-mcp"]). Steps and prerequisites: GitHub's MCP docs, Eclipse tab. Stock ADT without Copilot has no MCP client today.

Cursor · Windsurf · any MCP client — add this to its mcp.json / .mcp.json (project or global):

config.json

{
  "mcpServers": {
    "abap-mcp": { "command": "npx", "args": ["-y", "abap-mcp"] }
  }
}

Claude Desktop — Settings → Developer → Edit Config, add the same mcpServers block to claude_desktop_config.json, restart.

From a clone (contributing / hacking):

Terminal

npm install && npm run build
claude mcp add abap-mcp -- node /path/to/abap-mcp/dist/cli.js

Connected? Ask your agent "list your ABAP tools" — you should see all thirteen, lint_abap through get_abap_outline.

First things to ask

"Here's my functional spec — build the RAP implementation from it." (or run /mcp__abap-mcp__abap-from-spec)
"Lint this class against ABAP Cloud and explain the worst finding like I'm new to ABAP."
"How cloud-ready is this repo? Grade it and plan the migration in phases."
"Is MARA a released API? What do I use instead?"
"Scaffold a RAP BO for entity Booking on table zbooking, draft enabled."
"I reworked zcl_pricing — compare old vs new: did it actually get better?"

Guided workflows built in (MCP prompts)

The consultant's playbook ships both as four MCP prompts and as four Codex plugin skills. In Claude Code the prompts appear as slash commands (/mcp__abap-mcp__…); prompt-capable clients list them natively, while the Codex plugin discovers the corresponding skills:

Prompt	What it sets up
`abap-from-spec`	The blank-page killer. Hand it a functional/tech spec — or a plain-language requirement — and the agent builds working, validated modern ABAP/RAP: spec → build plan with an ASSUMPTION register → deterministic `scaffold_rap_bo` foundation → behavior logic → every file gated through `fix_abap` + `lint_abap` until clean → filled unit tests → delivery in activation order. Nothing unlinted is ever delivered.
`abap-review`	A full senior-consultant code review: lint → triage → explain each finding's why → minimal fixes → prove the rework with `compare_abap`. Optional `focus` (Performance / Security / Styleguide).
`abap-mentor`	Over-the-shoulder mentoring mode for the rest of the session: every snippet is quietly linted and readiness-checked, findings become plain-language guidance, new objects start from validated scaffolds.
`abap-migration-plan`	A client-ready phased migration plan driven by `plan_cloud_migration` — current state, phases with S/M/L efforts and exit criteria, released-API work separated — then offers to execute phase 1.

CLI — same engine, no AI required

Every tool is also a subcommand, so it works in terminals and CI where no MCP client exists:

Terminal

npx abap-mcp lint src/                          # lint files or whole directories
npx abap-mcp fix src/ --write                   # apply abaplint's deterministic auto-fixes in place
npx abap-mcp lint src/ --focus Performance      # themed pass: Performance | Security | Styleguide
npx abap-mcp lint src/ --rules-file org.json    # your org's abaplint rule pack, same engine
npx abap-mcp readiness src/ --fail-below 80     # repo-level ABAP Cloud readiness, scored + graded A–D
npx abap-mcp plan src/                          # phased migration backlog: work items, S/M/L efforts, exit criteria
npx abap-mcp unittest src/ --out tests/         # failing-by-default ABAP Unit skeletons for untested classes
npx abap-mcp deps src/ --mermaid                # dependency graph (+released-API flags) as a Mermaid diagram
npx abap-mcp compare old/ new/                  # rework verdict: findings resolved/introduced, grade movement
npx abap-mcp scaffold --entity Travel --table ztravel --key travel_id --out ./out
npx abap-mcp outline src/zcl_monster.clas.abap  # navigate big objects (--mermaid for a diagram)
npx abap-mcp released MARA I_Product            # released-API status + CDS successor
npx abap-mcp explain exit_or_check              # rule rationale

Directories are walked recursively (abapGit naming), batched automatically, and readiness merges batches into one scored, categorized repo report. Exit codes are CI-friendly (1 on error findings / failed threshold).

Agentic workflows, recipes & CI

docs/examples/abap2xlsx-assessment.md — what all of this produces on a real, well-known open-source repo (100 files, three commands, no system). docs/COOKBOOK.md — practical recipes: the fix-until-clean loop, PR review without a transport, whole-repo migration triage, CI gates, per-persona use cases. examples/claude-code/ — drop-in agentic workflows that turn the tools into that over-the-shoulder consultant: an abap-code-reviewer subagent, an abap-cloud-migrator sweep loop (readiness score as the loop condition), an abap-tech-debt-assessor (the graded A–D client deliverable), per-repo .mcp.json, and a GitHub Actions quality gate for abapGit repos.

Tools

Tool	What it does
`lint_abap`	abaplint static analysis over ABAP/CDS/BDEF sources → structured findings with rule docs links. Presets: `style` (default, snippet-friendly), `full`, `syntax-only`; per-rule overrides for org rule packs; `focus` lens (`Performance` / `Security` / `Styleguide`) for themed reviews.
`check_cloud_readiness`	Dual-parse diff (classic baseline vs `Cloud`): statements that are valid today but illegal in ABAP Cloud become categorized blockers (dynpro, list output, native SQL, …) with a transparent score and a density-banded A–D tech-debt grade; code broken at the baseline is reported separately, not counted as migration work. Also surfaces a separate, dated released-API cross-check (`releasedApiFindings`): direct access to non-released classic tables and deprecated-API usage found in the source, with CDS successor hints — informational, not folded into the score.
`fix_abap`	abaplint's own machine-applicable corrections, applied and verified: keyword casing, obsolete statements with defined modern replacements (`MOVE` → `=`, …). Batches re-parse after every pass and a batch that would break the parse is discarded — output is parser-guaranteed, never guessed. Unfixable findings return as `remaining` for judgment-tier rework (prove it with `compare_abap`).
`plan_cloud_migration`	The task-manager layer over readiness: arranges every blocker into a phased, consulting-ordered backlog — repair-the-baseline first, then mechanical quick wins, core rework, UI re-architecture, and a separate snapshot-dated released-API phase. Each work item carries an S/M/L effort band, a remediation recipe and sample locations; each phase carries objective, re-checkable exit criteria. Deterministic: same readiness numbers, rearranged — no new judgments.
`compare_abap`	Before/after verdict on a rework: lint findings resolved vs introduced (matched by content, so moved code isn't noise), blocker/score/grade movement, and classes/methods/FORMs added or removed. The objective referee for refactors and AI rewrites.
`check_released_api`	Looks up objects (tables, CDS views, function modules, classes, …) in SAP's bundled Cloudification snapshot → `released` / `deprecated` / `not-released` per object, plus a curated CDS successor for common classic tables. The released-API half of readiness, offline.
`scaffold_rap_bo`	Generates the canonical RAP managed-BO stack (root view, behavior definition `strict(2)` + optional draft, behavior class + handler locals, projection, metadata extension, OData V4 service definition) plus suggested table DDL, activation order and next steps.
`scaffold_abap_unit`	Generates the local ABAP Unit test class for each global class: setup + one skeleton test per public method, every skeleton failing loudly with a TODO so generated-but-empty tests can't masquerade as coverage. Round-tripped through abaplint with the class under test.
`get_object_dependencies`	Dependency graph over the provided sources — parser-level table/function references (annotated with released-API state + CDS successors), inherits/implements structure, and honestly-labeled textual cross-references. Optional Mermaid flowchart. The sequencing companion to `plan_cloud_migration`.
`list_abap_rules`	Browse abaplint's ~180 rules (filter by text or tag).
`explain_abap_rule`	One rule in depth — rationale (often Clean ABAP), examples, docs URL.
`format_abap`	Offline pretty-printer (keyword case + indentation).
`get_abap_outline`	Classes/methods/visibility/interfaces/FORMs of a source — navigate big objects without reading them whole. Optional Mermaid classDiagram output for instant structure visuals.

Honesty box — what this is not

Not ATC. The objective readiness score is still language-level: statements ABAP Cloud removed. Released-API coverage is now partial and offline: check_released_api and the releasedApiFindings in readiness reflect SAP's published Cloudification list as of the bundled snapshot date — they cover tables and function modules referenced in your source, not every API, and are only as current as the snapshot. A target system's own released-API list (ATC check API_RELEASE_STATE_CHECK / SAP_CP_READINESS) remains authoritative; treat an "absent from the list" result as "not released as of the snapshot", not as proof.
Scaffold validation is tiered. Generated classes and CDS views are round-tripped through abaplint at Cloud level before they're returned (the generator and the linter share one parser). Behavior/service definitions are outside abaplint's checked surface — they are golden-tested canonical templates, and ADT activation is the final arbiter. Each generated file is labeled validated: "abaplint" | "template".
Text-in only, by design. The analysis engine does no user-filesystem walking or outbound network access; it parses strings you explicitly pass. With stdio those strings are handled by the local child process. With Streamable HTTP they travel to the endpoint operator, so use HTTPS, authentication, and the documented privacy controls. For whole directories, use the CLI below, abaplint in CI, or the mcp-kit wrap-abaplint recipe.

Develop

Terminal

npm install
npm run check     # typecheck + tests + build + routing eval — the CI gate
node dist/cli.js  # stdio MCP server
npm run start:http # guarded Streamable HTTP on http://127.0.0.1:3000/mcp
npx @modelcontextprotocol/inspector --cli node dist/cli.js --method tools/list

Tool and prompt descriptions are CI-graded (a rubric test enforces verb-first names, when-to-use, non-goals, described params, worked examples — the mcp-kit discipline).

Design

The decision log — why offline, why abaplint, why a dual-parse readiness diff, why the scaffolder validates its own output, what was deliberately left out — lives in docs/DESIGN.md.

Related projects

abap-kit by Furkan Coşgun (MIT) — a CLI that scaffolds complete offline ABAP projects (abapGit layout, abaplint + transpiler config, the open-abap runtime) and can execute ABAP Unit tests locally via the abaplint transpiler. Complementary by design: abap-kit builds and runs the project harness; abap-mcp gives your AI agent the analysis, planning and scaffolding tools inside it — abap-kit create + abap-mcp setup is a complete offline ABAP+AI workspace. Its transpile-and-run pipeline is also the natural foundation for a future run_abap_unit tool here.

Credits

abaplint by Lars Hvam — the parser and rule engine underneath every tool here (MIT).
SAP/abap-atc-cr-cv-s4hc — SAP's official ABAP Cloudification Repository (object release list), Apache-2.0. The bundled released-API snapshot (src/data/released-apis.json, refreshed with each weekly release — tool output carries its snapshotDate) is a compact transform of that data, redistributed under Apache-2.0 with attribution; see docs/DESIGN.md and scripts/build-released-api-index.mjs for the pipeline.
mcp-kit — the production-MCP patterns this server follows (typed tool specs, transport discipline, description lint).

MIT © Akshay Palimkar. Not affiliated with or endorsed by SAP SE. "SAP", "ABAP" and "RAP" are trademarks of SAP SE; this is an independent open-source tool for developers working with them.