mcp-rap-migrator
Provides tools for migrating SAP Module Pool programs to RAP applications, leveraging SAP ADT REST APIs for analysis, code generation, and activation of ABAP objects.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-rap-migratorMigrate the module pool program SAPMZ_DEMO to RAP. Use package ZMIGRATED and prefix ZR_."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-rap-migrator
AI Agent that migrates SAP Module Pool programs → RAP applications, interactively.
Built on MCP (Model Context Protocol) + Anthropic Claude + SAP ADT REST APIs.
Architecture
Human Developer
↕ approves every step
Orchestrator Agent (Claude claude-sonnet-4-6)
↕ system prompt = MIGRATION_GUIDE.md (loaded once, token-efficient)
mcp-rap-migrator (THIS server) — write/transform tools
↕ delegates read-only calls to
mcp-abap-adt (mario-andreschak) — GetProgram, GetInclude, SearchObject
↕ both call
SAP ADT REST API /sap/bc/adt/
↕
SAP ABAP System (S/4HANA or BTP ABAP)Related MCP server: SAP ADT MCP Server
Why TWO MCP servers?
Server | Responsibility | Reason |
| Read: GetProgram, GetClass, SearchObject | Already built, battle-tested, reuse it |
| Write + Transform: analyze, generate, write, activate | New — wraps ADT write APIs + AI code generation |
Tools (this server)
Tool | Purpose | Step |
| Read + parse Module Pool → structured JSON | 1 |
| JSON analysis → CDS/BDef/Impl ABAP code strings | 2 |
| MANDATORY gate — shows human: what got, analysis, next action | Every step |
| Create Workbench Transport Request in SAP | 3 |
| PUT one ABAP object source via ADT REST | 4 |
| Activate objects, return syntax errors | 5 |
Token Efficiency Design
MIGRATION_GUIDE.mdloaded once as system prompt — not re-sent every callanalyze_module_poolreturns compact JSON (not raw ABAP source)human_checkpointshows only first 30 lines of code previewsErrors: only the error message, not the full XML response body
CSRF token reused across calls — not re-fetched every request
Prerequisites
SAP system with
/sap/bc/adtactive in SICFAlso install:
mcp-abap-adt—npx -y @smithery/cli install @mario-andreschak/mcp-abap-adt --client clineNode.js 20+ and npm
Setup
git clone <this-repo>
cd mcp-rap-migrator
npm install
npm run build
cp .env.example .env
# Edit .env with your SAP credentialsConfigure in Cline / Claude Desktop
{
"mcpServers": {
"mcp-abap-adt": {
"command": "node",
"args": ["C:/PATH/mcp-abap-adt/dist/index.js"],
"env": {
"SAP_URL": "https://your-sap.com:8000",
"SAP_USERNAME": "user",
"SAP_PASSWORD": "pass",
"SAP_CLIENT": "100"
}
},
"mcp-rap-migrator": {
"command": "node",
"args": ["C:/PATH/mcp-rap-migrator/dist/index.js"],
"env": {
"SAP_URL": "https://your-sap.com:8000",
"SAP_USERNAME": "user",
"SAP_PASSWORD": "pass",
"SAP_CLIENT": "100"
}
}
}
}Usage
In Cline or Claude Code, with MIGRATION_GUIDE.md loaded as system prompt:
Migrate the module pool program SAPMZ_DEMO to RAP.
Use package ZMIGRATED and prefix ZR_.The agent will:
Analyze the program → show you what it found → ask permission
Generate all RAP objects → show code preview → ask permission
Create a transport → write each object one-by-one → checkpoint each
Activate all → show results → checkpoint
You control every step.
Extending
Add new tools in src/tools/ and register them in src/index.ts.
Ideas:
generate_odata_service— expose the RAP BO as an OData V4 servicerun_atc_check— run ABAP Test Cockpit on generated objectscompare_behavior— run both old + new, compare DB results
mcp-rap-migrator
Available Tools
7 toolsanalyze_module_poolA
STEP 1 — Analyzes Module Pool source code fetched by mcp-abap-adt. IMPORTANT: First use mcp-abap-adt GetProgram to get program source, then GetInclude for each include, then pass combined source here. Returns structured JSON: screens, PAI/PBO modules, tables, LLM business analysis, PAI-to-RAP mapping.
| Name | Required | Description | Default |
|---|---|---|---|
| source_code | Yes | Combined ABAP source from mcp-abap-adt GetProgram + GetInclude calls | |
| program_name | Yes | SAP Module Pool program name e.g. ZSALES_ORDER_VIEWER |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description details the return value (structured JSON with screens, modules, etc.) but does not explicitly state whether the tool is read-only or has side effects. Since no annotations are provided, the description carries the burden; it is fairly transparent but could explicitly note non-destructive behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the purpose. Each sentence serves a clear function: stating the action, providing usage guidance, and summarizing output. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (analyzing modules pool with rich output) and the lack of an output schema, the description adequately covers what is returned. However, it could benefit from mentioning the structure of the JSON output more explicitly, but it remains complete enough for agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% already, so baseline is 3. The description adds context by explaining that source_code must be combined from GetProgram and GetInclude calls, and gives an example for program_name. This adds meaning beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: analyzing Module Pool source code. It explicitly mentions the resource (module pool source code) and the action (analyze). Sibling tools like check_released_cds or create_transport are unrelated, making this tool distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit prerequisites: first use GetProgram and GetInclude to fetch source, then pass the combined source here. This tells the agent exactly when to use this tool and what steps precede it, effectively differentiating from alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_released_cdsA
STEP 1b — MANDATORY before generate_rap_skeleton. Checks if SAP has released CDS views for the tables found in the Module Pool. Clean Core: always SELECT from released CDS instead of raw tables. Returns cds_source_mapping to pass into generate_rap_skeleton.
| Name | Required | Description | Default |
|---|---|---|---|
| tables | Yes | Tables from analyze_module_pool e.g. VBAK,VBAP,KONV |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must cover behavior. It states checks and returns mapping, which implies read-only. Could add details about side effects or permissions, but for a check tool this is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a key annotation about Clean Core. Front-loaded with step number and mandatory nature. Every sentence adds value, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given single parameter and no output schema, description fully explains purpose, input, output ('returns cds_source_mapping'), and workflow position. No gaps for AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter 'tables' with schema description already good (100% coverage). Description adds context that these come from analyze_module_pool, but no new syntax or format details beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'checks if SAP has released CDS views' and resource 'tables from Module Pool'. Mandatory step before generate_rap_skeleton distinguishes it from siblings like analyze_module_pool and generate_rap_skeleton.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly labeled 'STEP 1b — MANDATORY before generate_rap_skeleton' and gives rationale about Clean Core. Does not explicitly state when not to use, but context implies after analyze_module_pool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_transportA
Creates a Workbench Transport Request in SAP. Do this before write_abap_object. Returns transport number.
| Name | Required | Description | Default |
|---|---|---|---|
| description | Yes | Transport description e.g. 'RAP Migration of SAPMZ_DEMO' | |
| target_system | No | Target system SID e.g. Q01 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions that the tool returns a transport number, which is a behavioral detail. However, it does not disclose any side effects, authentication needs, or error conditions. The sequencing hint adds some value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, front-loading the purpose and usage guidance, then indicating the return value. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation tool with two parameters and no output schema, the description covers the essential purpose, sequencing, and return value. It does not mention error handling or prerequisites beyond the sequencing, but it is adequate given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description does not add any new information beyond the parameter descriptions already in the schema. The example values are also present in the schema, so no additional meaning is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'creates' and the resource 'Workbench Transport Request in SAP'. It also distinguishes from sibling tools by indicating it is a prerequisite before write_abap_object, and specifies the return value (transport number).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Do this before write_abap_object', providing clear guidance on when to use the tool. While it does not mention when not to use or alternatives, the context is sufficient for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_rap_skeletonA
STEP 2 — Given the analysis JSON from step 1, generates the full RAP migration plan: CDS view, Behavior Definition, Behavior Implementation class, metadata extensions. Returns ABAP code as strings — does NOT write to SAP yet. Human must approve.
| Name | Required | Description | Default |
|---|---|---|---|
| prefix | Yes | Z-prefix for generated objects e.g. ZR_ | |
| analysis_json | Yes | JSON string from analyze_module_pool | |
| target_package | Yes | SAP package for new objects e.g. ZMIGRATED |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It clearly states it does NOT write to SAP and requires human approval, which are critical behavioral traits. It does not mention any side effects or destructive actions, which is appropriate for a code-generation step.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words: the step number, action, what is generated, what is not done, and the approval gate are all present and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (generates multiple code artifacts) and no output schema, the description covers the essential components (CDS view, Behavior Definition, etc.) and the key constraint (no writes). It could be slightly more explicit about the return format, but is still fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good descriptions for each parameter. The description adds context by linking analysis_json to analyze_module_pool, but does not provide additional semantic depth beyond the schema defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a full RAP migration plan as ABAP code strings, identifying it as Step 2 and distinguishing it from siblings like analyze_module_pool (Step 1) and write_abap_object (actually writes to SAP).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use it (Step 2 after analysis) and that human approval is needed before writing. It implies when not to use through step context but lacks explicit exclusion statements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
human_checkpointA
MANDATORY between every step — shows the human: WHAT WAS DONE, ANALYSIS SUMMARY, and NEXT PROPOSED ACTION. Human must type YES/MODIFY/ABORT to proceed. Always call this before write_abap_object or validate_and_activate.
| Name | Required | Description | Default |
|---|---|---|---|
| step_title | Yes | ||
| what_i_got | Yes | Summary of data retrieved/generated | |
| my_analysis | Yes | Agent interpretation and migration decisions | |
| next_action | Yes | What agent will do next if approved | |
| code_preview | No | Optional: ABAP code snippet to show human (first 50 lines) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It discloses that the tool pauses for human input and shows specific summaries. Does not mention side effects, but the behavior is clear and non-destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no waste. Purpose and key usage details are front-loaded. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description fully covers the tool's role, when to use, required parameters, and what the human must do. No output schema is needed for this tool's simple interaction.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 80%, and the description maps its summary fields to parameters (e.g., 'ANALYSIS SUMMARY' to my_analysis) but adds little new detail beyond the schema's own descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool acts as a mandatory checkpoint showing the human what was done, analysis, and next action. It distinguishes from sibling tools by specifying it must be called before write_abap_object or validate_and_activate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states the tool must be used between every step and always before write_abap_object or validate_and_activate. Also tells the human must type YES/MODIFY/ABORT to proceed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_and_activateA
STEP 4 — Activates one or more ABAP objects via ADT REST. Runs syntax check first, returns errors for agent to fix before activation. Call human_checkpoint with results.
| Name | Required | Description | Default |
|---|---|---|---|
| objects | Yes | List of {type, name} to activate in order |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. States it runs syntax check first and returns errors for the agent to fix before activation, but does not clarify the exact outcome on success (e.g., what is returned after activation), whether activation is atomic, or if partial activation occurs. Missing output schema increases need for transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences that front-load the step number, purpose, and key behavioral info. Every sentence adds value with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema and description does not explain return values for success, only mentions error returns. Does not specify whether activation is atomic or partial, nor how this integrates with sibling tools like check_released_cds. Lacks sufficient detail for an activation tool in a workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter ('objects') with 100% schema coverage, so baseline is 3. Tool description adds no extra meaning beyond the schema's 'List of {type, name} to activate in order' – does not specify valid types or provide additional usage hints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it activates ABAP objects via ADT REST, is STEP 4 of a workflow, runs syntax check first, and returns errors. Distinguishes it from siblings like analyze_module_pool (analysis), check_released_cds (checking), create_transport (transport creation), generate_rap_skeleton (code generation), human_checkpoint (checkpoint), and write_abap_object (writing).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly indicates it's STEP 4, implying sequence, and instructs to call human_checkpoint with results. Provides clear context for use but does not explicitly mention when not to use or alternatives, though step numbering implies prerequisite steps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
write_abap_objectA
STEP 3 — Writes a single ABAP object to SAP via ADT REST. CRITICAL: Always follow this exact order: 1st=CDS Root View (DDLS), 2nd=CDS Child Views (DDLS), 3rd=Behavior Definition (BDEF), 4th=Implementation Class (CLAS), 5th=Metadata Extension (DDLS). NEVER write BDEF before CDS views. NEVER write CLAS before BDEF. One object at a time only.
| Name | Required | Description | Default |
|---|---|---|---|
| package | Yes | ||
| transport | Yes | Transport request number | |
| object_name | Yes | Object name in SAP | |
| object_type | Yes | ABAP object type | |
| source_code | Yes | Full ABAP/CDS source to write |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It reveals the critical ordering constraint and that it writes to SAP via ADT REST, but lacks details on side effects, error behavior, or prerequisites beyond order.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph with front-loaded purpose and critical rules. Uses all-caps for emphasis, though could be slightly more structured. Effective and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema or annotations, the description provides the essential ordering but misses return value info, error handling, and does not relate to sibling tools (e.g., when to use write vs validate_and_activate).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 80%, baseline 3. The description adds no extra detail per parameter beyond what the schema provides, though the ordering context indirectly relates to object_type. Marginal added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states specific verb 'writes' and resource 'ABAP object to SAP via ADT REST'. The critical order differentiates it from siblings like analyze_module_pool or check_released_cds, making its purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides a required sequence of object types with constraints like 'NEVER write BDEF before CDS views'. Also states 'One object at a time only', giving clear when-to-use and 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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
7 tool updates
v1.0.0- First observed
analyze_module_pool - First observed
check_released_cds - First observed
create_transport - First observed
generate_rap_skeleton - First observed
human_checkpoint - First observed
validate_and_activate - First observed
write_abap_object
TDQS
Each tool targets a distinct step in the migration workflow: analysis, CDS checking, transport creation, skeleton generation, human checkpoint, writing objects, and validation. No overlap or ambiguity.
Most tool names follow a verb_noun pattern (analyze_module_pool, check_released_cds, create_transport, generate_rap_skeleton, write_abap_object). However, 'human_checkpoint' is noun_noun and 'validate_and_activate' uses two verbs, breaking the pattern slightly.
7 tools cover the entire migration pipeline without being excessive. Each tool serves a necessary function, and the count is appropriate for the domain's complexity.
The tool set covers all essential steps from analysis through activation, including mandatory checkpoints. No obvious gaps for a migration workflow.
Maintenance
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