André — Analyse électorale française
Server Details
Résultats des élections françaises 1999-2026 par bureau de vote, socio-démo INSEE et cartes.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- joelgombin/andre-mcp
- GitHub Stars
- 0
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Tool Definition Quality
Score is being calculated. Check back soon.
Available Tools
11 toolscreate_data_tableTableau de donnéesIdempotentInspect
Crée un tableau de données formaté à partir de données structurées.
Utile pour présenter des résultats calculés ou combinés. Retourne un tableau texte formaté.
| Name | Required | Description | Default |
|---|---|---|---|
| rows | Yes | ||
| title | Yes | ||
| columns | Yes | ||
| description | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
export_dataExport de donnéesIdempotentInspect
Exporte des données électorales vers un fichier téléchargeable (CSV, JSON, TSV).
Deux modes : data (contenu inline) ou source_path (chemin vers fichier existant).
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | ||
| filename | Yes | ||
| file_format | No | csv | |
| source_path | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
generate_mapCarte électoraleIdempotentInspect
Génère une carte électorale (PNG) pour une élection.
Paramètres :
- election_id : identifiant élection (ex: '2024_legi_t1', '2020_muni_t2')
- metric : 'family' (famille politique en tête) ou 'nuance' (score d'une nuance)
- geography : 'bv' (bureau de vote, défaut) ou 'commune' (carte nationale)
- department : code département (ex: '13'). Requis pour geography='bv' sauf si commune fourni.
- commune : code commune (ex: '13055' pour Marseille). Centre la carte sur cette commune.
- nuance : code nuance quand metric='nuance' (ex: 'RN', 'LFI', 'ENS')
- region : code région pour geography='commune' (ex: '93' pour PACA)
Exemples :
- Carte par famille, Bouches-du-Rhône : election_id='2024_legi_t1', department='13'
- Carte score RN, Marseille : election_id='2024_legi_t1', commune='13055', metric='nuance', nuance='RN'
- Carte nationale : election_id='2024_euro_t1', geography='commune'
| Name | Required | Description | Default |
|---|---|---|---|
| canton | No | ||
| metric | No | family | |
| nuance | No | ||
| region | No | ||
| commune | No | ||
| geography | No | bv | |
| department | No | ||
| election_id | Yes | ||
| circonscription | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
query_adminDivisions administrativesARead-onlyIdempotentInspect
Requête les divisions administratives françaises.
Actions : search_commune, get_commune, search_postal,
list_epci, get_epci, list_cantons, list_departements, list_regions.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| epci_code | No | ||
| postal_code | No | ||
| search_term | No | ||
| commune_code | No | ||
| departement_code | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description does not need to repeat safety. It adds the list of actions, which specifies the available operations beyond annotations. No behavioral traits like rate limits, authentication, or error handling are mentioned, but the actions list is useful additional context.
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 very concise: two sentences with no wasted words. The first sentence states purpose, the second lists actions. It is front-loaded and easy to parse quickly.
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?
Despite having an output schema and annotations, the description is incomplete for an agent to correctly invoke the tool. The 6 parameters are not explained, and the only guidance is the list of action values. This is insufficient, especially given low schema coverage.
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 0%, so the description must compensate. Only the 'action' parameter is implied by the list of actions, but none of the other parameters (epci_code, postal_code, etc.) are explained. The description fails to add meaning beyond the schema, leaving an agent without parameter guidance.
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 queries French administrative divisions and lists specific actions (search_commune, get_commune, etc.). This distinguishes it from sibling query tools for other domains (elections, elus, etc.). The verb 'Requête' and resource 'divisions administratives françaises' are specific.
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 implies usage for administrative queries by listing actions but does not explicitly state when to use this tool versus alternatives like query_sql or query_dlp. No exclusions or when-not-to-use guidance is provided. The sibling context suggests specialization, but the description lacks explicit usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_dlpProfil social des candidats municipauxARead-onlyIdempotentInspect
Requête les données DLP (composition sociale des candidats municipaux 2020).
~546 000 candidats dans ~10 000 communes (≥1 000 hab.).
Classes : CDOM (dominant), CMOY (moyen), CSUB (subalterne), RET (retraité), AUTRES.
Actions : summary, composition, parite, listes, candidats, professions, sortants.
| Name | Required | Description | Default |
|---|---|---|---|
| sexe | No | ||
| action | Yes | ||
| classe | No | ||
| search | No | ||
| tetes_only | No | ||
| commune_code | No | ||
| sortants_only | No | ||
| departement_code | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the tool's safety profile is clear. The description adds context about data volume and class definitions, which enhances transparency but does not disclose additional behavioral traits like performance or rate limits.
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, using a short paragraph and a bullet list of actions. It front-loads the core purpose and data scope. However, the structure could be improved by grouping related parameters or adding inline hints.
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 8 parameters and an output schema, the description adequately covers the tool's data domain and action types, but lacks details on non-action parameters. The output schema exists, so return values are not needed in the description, but parameter explanations are incomplete.
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 description coverage is 0%, meaning the input schema provides no parameter descriptions. The description partially compensates for the 'action' parameter by listing valid values (summary, composition, etc.), but the other 7 parameters (sexe, classe, search, etc.) are left unexplained. This is insufficient for proper parameter understanding.
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 'Requête' (query) and the resource 'données DLP (composition sociale des candidats municipaux 2020)'. It explicitly lists the data size (~546k candidates) and classes, making the purpose distinct from sibling tools like query_admin or query_elections.
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?
No explicit guidance on when to use this tool over alternatives. The list of actions suggests common use cases, but there is no direct comparison or exclusion criteria. The sibling tool names in context partially compensate by indicating different data domains.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_electionsRésultats électorauxBRead-onlyIdempotentInspect
Requête les données électorales françaises (1999-2026).
Niveaux territoriaux : NATIONAL (aucun filtre), RÉGIONAL (region_code),
DÉPARTEMENTAL (departement_code), COMMUNAL (commune_code).
Actions de base : list_elections, query_results, list_bureaux, query_bureau,
query_by_bureau, rank_bureaux, list_circonscriptions, query_circonscription,
list_cantons, query_canton, search_candidate, query_candidatures, etc.
Actions « panel » (1 appel = analyse complète, évite les boucles) :
- compare_elections : compare deux scrutins pour un territoire
(election_id + compare_to_election + commune_code|departement_code,
candidate_name optionnel).
- query_all_circonscriptions : vainqueur de CHAQUE circonscription d'un
territoire en un appel (election_id + commune_code|departement_code,
législatives uniquement).
- vote_reserve : score d'une famille + abstention par bureau de vote sur
les scrutins récents comparables (commune_code + famille).
- select_communes : sélectionne/classe des communes par critères géo +
population + électoraux (region_code/departement_code/epci/commune_codes,
population_min/max, commune_metric, condition, sort_by, limit, order ;
commune_metric/condition nécessitent election_id).
- cross_election_panel : évolution d'un sujet (famille ou nuance_code) par
commune sur N scrutins (elections=ids séparés par des virgules + scope
commune_code/departement_code/region_code/commune_codes).
- bureau_breakdown : pivot par bureau (top_n nuances/blocs + participation,
with_sociodem optionnel) pour commune_code + election_id.
| Name | Required | Description | Default |
|---|---|---|---|
| epci | No | ||
| tour | No | ||
| limit | No | ||
| order | No | ||
| top_n | No | ||
| action | Yes | ||
| offset | No | ||
| famille | No | ||
| sort_by | No | ||
| bureau_id | No | ||
| by_family | No | ||
| condition | No | ||
| elections | No | ||
| bureau_code | No | ||
| canton_code | No | ||
| election_id | No | ||
| family_name | No | ||
| list_search | No | ||
| nuance_code | No | ||
| rank_metric | No | ||
| region_code | No | ||
| commune_code | No | ||
| nuance_level | No | ||
| scrutin_type | No | ||
| commune_codes | No | ||
| with_sociodem | No | ||
| candidate_name | No | ||
| commune_metric | No | ||
| population_max | No | ||
| population_min | No | ||
| candidate_query | No | ||
| use_ferd_coding | No | ||
| candidate_search | No | ||
| departement_code | No | ||
| compare_to_election | No | ||
| circonscription_code | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description reinforces a query-only behavior. No extra behavioral details are provided (e.g., authentication, rate limits). Given strong annotations, the description adds limited value but does not contradict.
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 front-loaded with a clear purpose, but then becomes a dense reference list of actions. While it is structured with headers, it is lengthy and could be more concise by separating action details into a separate section. The bullet format helps readability but adds length.
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 complexity (36 parameters, many actions, output schema exists), the description is incomplete. It does not explain output structure, pagination, error handling, or how to combine parameters across actions. The output schema may partially compensate, but the description lacks sufficient guidance for correct tool invocation.
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 description coverage is 0%, meaning the input schema provides no parameter descriptions. The description mentions parameters like 'election_id', 'commune_code', etc. only in context of actions, but does not explain their types, formats, or constraints. With 36 parameters and no schema descriptions, this is insufficient for an AI to understand parameter semantics.
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 title 'Résultats électoraux' and the first sentence 'Requête les données électorales françaises (1999-2026)' clearly state the tool's purpose. It is distinct from sibling tools which are for other types of queries (admin, sociodem, etc.). However, the extensive list of actions somewhat obscures the core purpose.
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 distinguishes between 'Actions de base' and 'Actions « panel »' with brief explanations for panel actions (e.g., '1 appel = analyse complète, évite les boucles'). However, it does not provide guidance on when to use this tool versus other query tools, nor does it help choose among the many actions for a given task.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_elusÉlus de la RépubliqueRead-onlyIdempotentInspect
Requête les élus de la République française (base BRÉF).
Actions : search_elu, list_mandate_types, list_elus.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| search_term | No | ||
| mandate_type | No | ||
| departement_code | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
query_sociodemDonnées socio-démographiquesBRead-onlyIdempotentInspect
Requête les données socio-démographiques au niveau bureau de vote.
Données INSEE RP 2022 + Filosofi 2021, interpolées IRIS→BDV.
Actions : list_variables, profile, indices, rank, compare.
| Name | Required | Description | Default |
|---|---|---|---|
| order | No | ||
| action | Yes | ||
| variable | No | ||
| commune_code | No | ||
| commune_codes | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable context about data sources (INSEE RP 2022 + Filosofi 2021, interpolated IRIS→BDV) and lists available actions, which aids understanding. No contradiction with annotations.
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 (two lines plus a bullet list) and front-loaded with the main purpose. It could be more structured, but it efficiently conveys the tool's capability without 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 has 5 parameters with no schema descriptions and no enum hints, and an output schema exists, the description lacks details on parameter usage, examples, or return format. The list of actions helps but is insufficient for complete guidance.
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 description coverage is 0% for 5 parameters. The description only mentions possible values for the 'action' parameter, providing no meaning for 'order', 'variable', 'commune_code', or 'commune_codes'. With low schema coverage, the description fails to compensate adequately.
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 'Requête les données socio-démographiques au niveau bureau de vote' (query socio-demographic data at polling station level), specifying the verb, resource, and scope. It distinguishes from sibling tools like query_admin or query_elections by focusing on socio-demographic data, and lists specific actions.
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 lists possible actions (list_variables, profile, indices, rank, compare) but provides no guidance on when to use this tool versus siblings or how to choose among the actions. No explicit usage context or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_sqlRequête SQL (lecture seule)Read-onlyIdempotentInspect
Exécute une requête SQL directe sur la base DuckDB (read-only).
Tables principales :
- general_results : résultats généraux par bureau de vote
- candidats_results : résultats par candidat par bureau de vote
- elections_disponibles : liste des élections (id_election, nb_bureaux, total_inscrits)
- candidats_avec_nuances : candidats avec famille politique (si nuances enrichies)
- resultats_par_famille : résultats agrégés par famille politique
- communes, epci, departements, regions : divisions administratives
- bv_sociodemographique : données socio-démo par bureau de vote
ATTENTION — colonnes de general_results (noms avec espaces, à quoter) :
id_election, id_brut_miom, "Code du département", "Code de la commune" (SANS préfixe dept, ex: '055' pour Marseille),
"Libellé de la commune", Inscrits, Abstentions, Votants, Blancs, Nuls, Exprimés.
PRÉFÉRER query_elections pour les analyses standard — query_sql est pour les requêtes ad hoc avancées.
Exemple :
SELECT id_election, ROUND(100.0 * SUM(Abstentions) / NULLIF(SUM(Inscrits), 0), 1) as abstention_pct
FROM general_results WHERE "Code du département" = '13' AND "Code de la commune" = '055'
GROUP BY id_election ORDER BY id_election DESC LIMIT 5
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
simulate_fusionsSimulation de fusions de listesRead-onlyIdempotentInspect
Simule les scénarios de fusion de listes municipales entre T1 et T2.
Actions : 'status' (classer les listes après T1), 'simulate' (projections T2).
Uniquement pour les élections municipales.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| election_id | Yes | ||
| report_rate | No | ||
| commune_code | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
visualizeVisualisation graphiqueCIdempotentInspect
Crée une visualisation Plotly (retourne le spec JSON).
Deux modes :
- Spec libre : fournir 'spec' (dict Plotly complet {data, layout})
- Assisté : fournir chart_type + data + x + y
Types supportés : bar, line, scatter, histogram, box, violin, heatmap, treemap.
| Name | Required | Description | Default |
|---|---|---|---|
| x | No | ||
| y | No | ||
| data | No | ||
| spec | No | ||
| color | No | ||
| title | No | ||
| data_file | No | ||
| chart_type | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate idempotentHint=true and destructiveHint=false. The description adds no additional behavioral context (e.g., side effects, permissions, limitations). It merely restates the return format.
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?
Concise with front-loaded purpose and bulleted modes. However, could be more structured to cover all parameters efficiently.
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 8 parameters and no schema descriptions, the description is incomplete. It does not explain data_file, the role of color/title, or return value structure beyond 'spec JSON'. Lacks completeness for a complex tool.
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 description coverage is 0%, so the description must explain parameters. It mentions spec, chart_type, data, x, y, but omits data_file, color, title in detail. Missing semantics for 5 of 8 parameters.
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 function: create a Plotly visualization and return its JSON spec. It distinguishes two modes and lists supported chart types. However, it does not explicitly differentiate from sibling tools like generate_map or create_data_table.
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?
No guidance on when to use the 'spec libre' vs 'assisté' mode, or when not to use this tool. No comparison to alternatives or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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